Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Machine Vision and Applications
Erschienen in: Machine Vision and Applications 6/2014

01.08.2014 | Original Paper

Super-resolution: a comprehensive survey

verfasst von: Kamal Nasrollahi, Thomas B. Moeslund

Erschienen in: Machine Vision and Applications | Ausgabe 6/2014

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Super-resolution, the process of obtaining one or more high-resolution images from one or more low-resolution observations, has been a very attractive research topic over the last two decades. It has found practical applications in many real-world problems in different fields, from satellite and aerial imaging to medical image processing, to facial image analysis, text image analysis, sign and number plates reading, and biometrics recognition, to name a few. This has resulted in many research papers, each developing a new super-resolution algorithm for a specific purpose. The current comprehensive survey provides an overview of most of these published works by grouping them in a broad taxonomy. For each of the groups in the taxonomy, the basic concepts of the algorithms are first explained and then the paths through which each of these groups have evolved are given in detail, by mentioning the contributions of different authors to the basic concepts of each group. Furthermore, common issues in super-resolution algorithms, such as imaging models and registration algorithms, optimization of the cost functions employed, dealing with color information, improvement factors, assessment of super-resolution algorithms, and the most commonly employed databases are discussed.
Vorheriger Artikel Automatic optical phase identification of micro-drill bits based on improved ASM and bag of shape segment in PCB production
Nächster Artikel Fast automatic medical image segmentation based on spatial kernel fuzzy c-means on level set method

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Gerchberg, R.W.: Super-resolution through error energy reduction. J. Mod. Opt. 21(9), 709–720 (1974)
2.
Santis, P.D., Gori, F.: On an iterative method for super-resolution. J. Mod. Opt. 22(8), 691–695 (1975)
3.
Tsai, R., Huang, T.: Multiframe image restoration and registration. In: Tsai, R.Y., Huang, T.S. (eds.) Advances in Computer Vision and Image Processing, vol. 1, pp. 317–339. JAI Press Inc., Stamford (1984)
4.
Mjolsness, E.: Neural networks, pattern recognition, and fingerprint hallucination. PhD thesis, California Institute of Technology (1985).
5.
Peleg, S., Keren, D., Schweitzer, L.: Improving image resolution using subpixel motion. Pattern Recognit. Lett. 5(3), 223–226 (1987)
6.
Keren, D., Peleg, S., Brada, R.: Image sequence enhancement using subpixel displacements. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 742–746 (1988).
7.
Stark, H., Oskoui, P.: High-resolution image recovery from image-plane arrays, using convex projections. J. Opt. Soc. Am. A 6(11), 1715–1726 (1989)
8.
Irani, M., Peleg, S.: Super-resolution from image sequences. In: Proceedings of IEEE International Conference on Pattern Recognition, USA, pp. 115–120 (1990).
9.
Kim, S., Bose, N., Valenzuela, H.M.: Recursive reconstruction of high resolution image from noisy undersampled multiframes. IEEE Trans. Acoust. Speech Signal Process. 38(6), 1013–1027 (1990)
10.
Luttrell, S.P.: Bayesian autofocus/super-resolution theory. In: Proceedings of IEE Colloquium on Role of Image Processing in Defence and Military Electronics, pp. 1–6 (1990).
11.
Aizawa, K., Komatsu, T., Saito, T.: Acquisition of very high resolution images using stereo cameras. Proc. SPIE Vis. Commun. Image Process. 1605, 318–328 (1991)
12.
Hunt, B.R.: Imagery super-resolution: emerging prospects. Proceedings of SPIE on Applications of Digital Image Processing XIV, USA 1567, 600–608 (1991)
13.
Irani, M., Peleg, S.: Improving resolution by image registration. CVGIP Graph. Mod. Image Process. 53, 231–239 (1991)
14.
Irani, M., Peleg, S.: Image sequence enhancement using multiple motions analysis. In: Proceedings of International Conference on Computer Vision and Pattern Recognition, pp. 216–222 (1992).
15.
Schatzberg, A., Devaney, A.J.: Super-resolution in diffraction tomography. Inverse Probl. 8, 149–164 (1992)MATHMathSciNet
16.
Tekalp, A.M., Ozkan, M., Sezan, M.: High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration. Proceedings of the IEEE International Conference on Acousics, Speech and Signal Processing, USA III, 169–172 (1992)
17.
Ur, H., Gross, D.: Improved resolution from sub-pixel shifted pictures. CVGIP Graph. Mod. Image Process. 54, 181–186 (1992)
18.
Aghajan, H.K., Kailath, T.: Sensor array processing techniques for super-resolution multi-line-fitting and straight edge detection. IEEE Trans. Image Process. 2(4), 454–465 (1993)
19.
Bose, N., Kim, H., Valenzuela, H.: Recursive implementation of total least squares algorithm for image reconstruction from noisy, undersampled multiframes. Proceedings of the IEEE Conference on Acoustics, Speech and Signal Processing, USA 5, 269–272 (1993)
20.
Irani, M., Peleg, S.: Motion analysis for image enhancement: resolution, occlusion, and transparency. J. Vis. Commun. Image Represent. 4, 324–335 (1993)
21.
Bose, N., Kim, H., Zhou, B.: Performance analysis of the TLS algorithm for image reconstruction from a sequence of undersampled noisy and blurred frames. Proceedings of the IEEE International Conference on Image Processing, USA III , 571–575 (1994)
22.
Cheeseman, P., Kanefsky, B., Kraft, R., Stutz, J.: Super-resolved surface reconstruction from multiple images. Technical Report FIA9412, NASA (1994).
23.
Fussfeld, E., Zeevi, Y.Y.: Super-resolution estimation of edge images. Proc. Int. Conf. Comput. Vis. Image Process. 1, 11–16 (1994).
24.
Mann, S., Picard, R.: Virtual bellows: constructing high quality stills from video. In: Proceedings of the IEEE International Conference on Image Processing (1994).
25.
Schultz, R.R., Stevenson, R.L.: A Bayesian approach to image expansion for improved definition. IEEE Trans. Image Process. 3(3), 233–242 (1994)
26.
Walsh, D.O., Nielsen-Delaney, P.A.: A direct method for super-resolution. J. Opt. Soc. Am. A 11, 572–579 (1994)
27.
Sauer, K.D., Borman, S., Bouman, C.A.: Parallel computation of sequential pixel updates in statistical tomographic reconstruction. Proceedings of the IEEE International Conference on Image Processing, USA 2, 93–96 (1995)
28.
Shekarforoush, H., Berthod, M., Zerubia, J.: 3D super-resolution using generalized sampling expansion. Proceedings of the IEEE International Conference on Image Processing, USA 2, 300–303 (1995)
29.
Bascle, B., Blake, A., Zisserman, A.: Motion deblurring and super-resolution from an image sequence. In: Proceedings of 4th European Conference on Computer Vision, UK, pp. 312–320 (1996).
30.
Chiang, M.C., Boult, T.E.: Efficient image warping and super-resolution. In: Proceedings of 3rd IEEE Workshop on Applications of Computer Vision, USA, pp. 56–61 (1996).
31.
Elad, M., Feuer, A.: Super-resolution reconstruction of an image. In: Proceedings of 19th IEEE Conference on Electrical and Electronics Engineers, Israel, pp. 391–394 (1996).
32.
Miller, C., Hunt, B.R., Kendrick, R.L., Duncan, A.L.: Reconstruction and super-resolution of dilute aperture imagery, In: Proceedings of International Conference on Image Processing, Switzerland (1996).
33.
Shekarforoush, H., Berthod, M., Zerubia, J., Werman, M.: Sub-pixel Bayesian estimation of albedo and height. Int. J. Comput. Vis. 19(3), 289–300 (1996)
34.
Schultz, R.R., Stevenson, R.L.: Extraction of high-resolution frames from video sequences. IEEE Trans. Image Process. 5(6), 996–1011 (1996)
35.
Tom, B.C., Katsaggelos, A.: Resolution enhancement of video sequences using motion compensation. Proceedings of the IEEE International Conference on Image Processing, Switzerland I, 713–716 (1996)
36.
Chiang, M.C., Boult, T.E.: Imaging-consistent super-resolution. In: Proceedings of the DARPA Image Understanding Workshop (1997).
37.
Chiang, M.C., Boult, T.E.: Local blur estimation and super-resolution. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition, Puerto Rico, pp. 821–826 (1997).
38.
Elad, M., Feuer, A.: Restoration of a single super-resolution image from several blurred, noisy, and under-sampled measured images. IEEE Trans. Image Process. 6(12), 1646–1658 (1997)
39.
Eren, P.E., Sezan, M.I., Tekalp, A.M.: Robust object-based high-resolution image reconstruction from low-resolution video. IEEE Trans. Image Process. 6(10), 1446–1451 (1997)
40.
Green, J.J., Hunt, B.R.: Super-resolution in a synthetic aperture imaging system. Proc. Int. Conf. Image Process. 1, 865–868 (1997)
41.
Hardie, R.C., Barnard, K.J., Armstrong, E.E.: Joint MAP registration and high-resolution image estimation using a sequence of under sampled images. IEEE Trans. Image Process. 6, 1621–1633 (1997)
42.
Hong, M.C., Kang, M.G., Katsaggelos, A.K.: A regularized multichannel restoration approach for globally optimal high resolution video sequence. SPIE VCIP 3024, 1306–1317 (1997)
43.
Hong, M.C., Kang, M.G., Katsaggelos, A.K.: An iterative weighted regularized algorithm for improving the resolution of video sequences. Proc. Int.l Conf. Image Process. 2, 474–477 (1997).
44.
Lorette, A., Shekarforoush, H., Zerubia, J.: Super-resolution with adaptive regularization. Proceedings of the IEEE International Conference on Image Processing, USA 1, 169–172 (1997)
45.
Patti, A.J., Sezan, M.I., Tekalp, A.M.: Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time. IEEE Trans. Image Proces. 6(8), 1064–1076 (1997)
46.
Sheppard, D., Hunt, B.R., Marcellin, M.W.: Super-resolution of imagery acquired through turbulent atmosphere. In: Proceedings of 13th IEEE Conference on Signals, Systems and Computers, USA, vol. 1, pp. 81–85 (1997).
47.
Borman, S., Stevenson, R.L.: Spatial resolution enhancement of low-resolution image sequences. A comprehensive review with directions for future research. Laboratory of Image and Signal Analysis, University of Notre Dame, Technical Report (1998).
48.
Borman, S., Stevenson, R.L.: Super-resolution from image sequences: a review. In: Proceedings of Midwest Symposium on Circuits and Systems, pp. 374–378 (1998).
49.
Calle, D., Montanvert, A.: Super-resolution inducing of an image. Proc. IEEE Int. Conf. Image Process. 3, 232–235 (1998)
50.
Capel, D., Zisserman, A.: Automated mosaicing with super-resolution zoom. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition, pp. 885–891 (1998).
51.
Hardie, R.C., Barnard, K.J., Bognar, J.G., Armstrong, E.E., Watson, E.A.: High-resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system. Opt. Eng. 37(1), 247–260 (1998)
52.
Pastina, D., Farina, A., Gunning, J., Lombardo, P.: Two-dimensional super-resolution spectral analysis applied to SAR images. IEE Proc. Radar Sonar Navig. 145(5), 281–290 (1998)
53.
Patti, A., Altunbasak, Y.: Artifact reduction for POCS-based super-resolution with edge adaptive regularization and higher-order interpolants. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 217–221 (1998).
54.
Pohl, C., Van Genderen, J.L.: Multisensor image fusion in remote sensing: concepts, methods and applications. Int. J. Remote Sens. 19(5), 823–854 (1998)
55.
Schultz, R.R., Meng, L., Stevenson, R.L.: Subpixel motion estimation for super-resolution image sequence enhancement. J. Vis. Commun. Image Represent. 9(1), 38–50 (1998)
56.
Zomet, A., Peleg, S.: Applying super-resolution to panoramic mosaics. In: Proceedings of 4th IEEE Workshop on Applications of Computer Vision (1998).
57.
Baker, S., Kanade, T.: Hallucinating faces. Technical Report CMU-RI-TR-99-32. The Robotics Institute, Carnegie Mellon University, USA (1999).
58.
Baker, S., Kanade, T.: Super-resolution optical flow. Technical Report CMU-RI-TR-99-36. The Robotics Institute, Carnegie Mellon University, USA (1999).
59.
Bi, Z., Liu, Z.: Super resolution SAR imaging via parametric spectral estimation methods. IEEE Trans. Aerosp. Electron. Syst. 35(1), 267–281 (1999)
60.
Borman, S., Stevenson, R.L.: Simultaneous multi-frame MAP super-resolution video enhancement using spatio temporal priors. In: Proceedings of IEEE International Conference on Image Processing, Japan, pp. 469–473 (1999).
61.
Candocia, F.M., Principe, J.C.: Super-resolution of images based on local correlations. IEEE Trans. Neural Netw. 10(2), 372–380 (1999)
62.
Elad, M., Feuer, A.: Super-resolution reconstruction of image sequences. IEEE Trans. Pattern Anal. Mach. Intell. 21(9), 817–834 (1999)
63.
Elad, M., Feuer, A.: Super-resolution reconstruction of continuous image sequences. Proceedings of International Conference on Image Processing, Japan 3, 459–463 (1999)
64.
Elad, M., Feuer, A.: Super-resolution restoration of an image sequence: adaptive filtering approach. IEEE Trans. Image Process. 8, 387–395 (1999)
65.
Freeman, W.T., Pasztor, E.C.: Learning to estimate scenes from images. In: Kearns, M.S., Solla, S.A., Cohn, D.A. (eds.) Advances in Neural Information Processing Systems, vol. 11. Cambridge (1999).
66.
Freeman, W.T., Pasztor, E.: Markov networks for low-level vision. Mitsubishi Electric Research Laboratory Technical, Report TR99-08 (1999).
67.
Hunt, B.R.: Super-resolution of imagery: understanding the basis for recovery of spatial frequencies beyond the diffraction limit. In: Proceedings of Information, Decision and Control, Australia (1999).
68.
Nguyen, N., Milanfar, P., Golub, G.: Blind super-resolution with generalized cross-validation using gauss-type quadrature rules. In: Proceedings of the 33rd Asilomar Conference on Signals, Systems, and Computers (1999).
69.
Pan, M.C., Lettington, A.H.: Efficient method for improving Poisson MAP super-resolution. Electron. Lett. 35, 803–805 (1999)
70.
Shekarforoush, H., Chellappa, R.: Data-driven multi-channel super-resolution with application to video data. J. Opt. Soc. Am. A 16(3), 481–492 (1999)
71.
Baker, S., Kanade, T.: Hallucinating faces. In: Proceedings of 4th IEEE International Conference on Automatic Face and Gesture Recognition, France, pp. 83–88 (2000).
72.
Bhattacharjee, S., Sundareshan, M.K.: Modeling and extrapolation of prior scene information for set-theoretic restoration and super-resolution of diffraction-limited images. In: Proceedings of the IEEE International Conference on Image Processing, Canada (2000).
73.
Capel, D., Zisserman, A.: Super-resolution enhancement of text image sequences. In: Proceedings of the International Conference on Pattern Recognition, Spain (2000).
74.
Chiang, M.C., Boult, T.E.: Efficient super-resolution via image warping. Image Vis. Comput. 18, 761–771 (2000)
75.
Cohen, B., Dinstein, I.: Polyphase back-projection filtering for image resolution enhancement. IEE Proc. Vis. Image Signal Process. 147, 318–322 (2000)
76.
Freeman, W.T., Pasztor, E.C., Carmichael, O.T.: Learning low-level vision. Int. J. Comput. Vis. 20(1), 25–47 (2000)
77.
Gee, T.F., Karnowski, T.P., Tobin, K.W.: Multiframe combination and blur deconvolution of video data. Proc. SPIE Image Video Commun. Process. 3974, 788–795 (2000)
78.
Nguyen, N.X.: Numerical algorithms for image super-resolution. PhD thesis, Stanford University (2000).
79.
Nguyen, N., Milanfar, P.: An efficient wavelet-based algorithm for image super-resolution. In: Proceedings of the IEEE International Conference on Image Processing, vol. II, Canada, pp. 351–354 (2000).
80.
Smelyanskiy, V., Cheeseman, P., Maluf, D., Morris, R.: Bayesian super-resolved surface reconstruction from images. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, USA (2000).
81.
Zomet, A., Peleg, S.: Efficient super-resolution and applications to mosaics. In: Proceedings of IEEE International Conference on Pattern Recognition, Spain, pp. 579–583 (2000).
82.
Baker, S., Kanade, T.: Super-resolution: reconstruction or recognition? In: Proceedings of IEEE EURASIP Workshop on Nonlinear Signal and Image Processing, USA (2001).
83.
Bose, N.K., Lertrattanapanich, S., Koo, J.: Advances in superresolution using \(L\)-curve. Proc. Int. Symp. Circuits Syst. 2, 433–436 (2001)
84.
Capel, D.P.: Image mosaicing and super-resolution. PhD thesis, University of Oxford (2001).
85.
Capel, D.P., Zisserman, A.: Super-resolution from multiple views using learnt image models. Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, USA 2, 627–634 (2001)
86.
Dekeyser, F., Bouthemy, P., Perez, P.: A new algorithm for super-resolution from image sequences. In: Proceeding of International Conference on Computer Analysis of Images and Patterns, Germany, pp. 473–481 (2001).
87.
Elad, M., Hel-Or, Y.: A fast super-resolution reconstruction algorithm for pure translational motion and common space-invariant blur. IEEE Trans. Image Process. 10(8), 1187–1193 (2001)MATH
88.
Kim, H., Jang, J.H., Hong, K.S.: Edge-enhancing super-resolution using anisotropic diffusion. In: Proceedings of IEEE International Conference on Image Processing, Greece, pp. 130–133 (2001).
89.
Lin, Z., Shum, H.Y.: On the fundamental limits of reconstruction-based super-resolution algorithms. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA, pp. 1171–1176 (2001).
90.
Liu, C., Shum, H.Y., Zhang, C.S.: A two-step approach to hallucinating faces: global parametric model and local nonparametric model. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA 1, 192–198 (2001)
91.
Nguyen, N., Milanfar, P., Golub, G.: A computationally efficient super-resolution image reconstruction algorithm. IEEE Trans. Image Process. 10, 573–583 (2001)MATHMathSciNet
92.
Nguyen, N., Milanfar, P., Golub, G.: Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement. IEEE Trans. Image Process. 10, 1299–1308 (2001)MATHMathSciNet
93.
Patti, A.J., Altunbasak, Y.: Artifact reduction for set theoretic super-resolution image reconstruction with edge adaptive constraints and higher-order interpolants. IEEE Trans. Image Process. 10(1), 179–186 (2001)
94.
Rajan, D., Chaudhuri, S.: Generalized interpolation and its applications in super-resolution imaging. Image Vis. Comput. 19, 957–969 (2001)
95.
Rajan, D., Chaudhuri, S.: Generation of super-resolution images from blurred observations using Markov random fields. Proceedings of IEEE International Conference on Acoustics, Speech, Signal Processing, USA 3, 1837–1840 (2001)
96.
Tatem, A.J., Lewis, H.G., Atkinson, P.M., Nixon, M.S.: Super-resolution target identification from remotely sensed images using a Hopfield neural network. IEEE Trans. Geosci. Remote Sens. 39(4), 781–796 (2001)
97.
Zomet, A., Rav-Acha, A., Peleg, S.: Robust super-resolution. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, USA, vol. 1, pp. 645–650 (2001).
98.
Altunbasak, Y., Patti, A.J., Mersereau, R.M.: Super-resolution still and video reconstruction from mpeg-coded video. IEEE Trans. Circuits Syst. Video Technol. 12, 217–226 (2002)
99.
Baker, S., Kanade, T.: Limits on super-resolution and how to break them. IEEE Trans. Pattern Anal. Mach. Intell. 24(9), 1167–1183 (2002)
100.
Baker, S., Kanade, T.: Super-resolution: limits and beyond. In: Chaudhuri, S. (ed.) Super-Resolution Imaging, ch. 10, pp. 244–276. Kluwer Academic, Norwell (MA) (2002).
101.
Chaudhuri, S.: Super-Resolution Imaging. Kluwer Academic, Norwell (MA) (2002)
102.
Freeman, W.T., Jones, T.R., Pasztor, E.C.: Example-based super-resolution. IEEE Comput. Graph. Appl. 22(2), 56–65 (2002)
103.
Gilboa, G., Sochen, N.: Zeevi, Ye Y.: Forward-and-backward diffusion processes for adaptive image enhancement and denoising. IEEE Trans. Image Process. 11(7), 689–703 (2002)
104.
Gunturk, B.K., Altunbasak, Y., Mersereau, R.M.: Multiframe resolution-enhancement methods for compressed video. IEEE Signal Process. Lett. 9, 170–174 (2002)
105.
Gunturk, B.K., Batur, A.U., Altunbasak, Y., Hayes, M.H., Mersereau, R.M.: Eigenface-based super-resolution for face recognition. Proceedings of International Conference on Image Processing, USA 2, 845–848 (2002)
106.
Komatsu, T., Aizawa, K., Saito, T.: Resolution enhancement using multiple apertures. In: Chaudhuri, S. (ed.) Super-Resolution Imaging, pp. 171–193. Kluwer Academic, Norwell (MA) (2002)
107.
Rajan, D., Chaudhuri, S.: An MRF-based approach to generation of super-resolution images from blurred observations. J. Math. Imaging Vis. 16(1), 5–15 (2002)MATHMathSciNet
108.
Rajan, D., Chaudhuri, S.: Data fusion techniques for super-resolution imaging. Inf. Fusion 3(1), 25–38 (2002)MathSciNet
109.
Rajan, D., Chaudhuri, S.: Super-resolution imaging using blur as a cue. In: Chaudhuri, S. (ed.) Super-Resolution Imaging, ch. 5, pp. 107–129. Kluwer, Norwell (2002).
110.
Segall, C.A., Katsaggelos, A.K., Molina, R., Mateos, J.: Super-resolution from compressed video. In: Chaudhuri, S. (ed.) Super-Resolution Imaging, pp. 211–242. Kluwer, Boston (2002)
111.
Storkey, A.J.: Dynamic structure super-resolution. Adv. Neural Inf. Process. Syst. 16, 1295–1302 (2002)
112.
Tipping, M.E., Bishop, C.M.: Bayesian image super-resolution. Adv. Neural Inf. Process. Syst. 15, 1303–1310 (2002)
113.
Tom, B.C., Galatsanos, N.P., Katsaggelos, A.K.: Reconstruction of a high resolution image from multiple low resolution images. In: Chaudhuri, S. (ed.) Super-Resolution Imaging, ch. 4, pp. 73–105, ch. 4, pp. 73–105. Kluwer, Norwell (2002).
114.
Zhang, Y.: Problems in the fusion of commercial high resolution satellite images as well as Landsat 7 images and initial solutions. Proc. Int. Arch. Photogramm. Remote Sens. 34(4), 9–12 (2002)
115.
Zhao, W., Sawhney, H.S.: Is super-resolution with optical flow feasible? In: Proceedings of European Conference on Computer Vision, Denmark (2002).
116.
Zhao, W., Sawhney, H., Hansen, M., Samarasekera, S.: Super-fusion: a super-resolution method based on fusion. Proceedings of IEEE International Conference on Pattern Recognition, Canada 2, 269–272 (2002)
117.
Zomet, A., Peleg, S.: Multi-sensor super-resolution. In: Proceedings of 6th IEEE Workshop on Applications of Computer Vision, USA, pp. 27–31 (2002).
118.
Zomet, A., Peleg, S.: Super-resolution from multiple images having arbitrary mutual motion. In: Chaudhuri, S. (ed.) Super-Resolution Imaging, pp. 195–209. Kluwer Academic, Norwell (MA) (2002)
119.
Abad, J., Vega, M., Molina, R., Katsaggelos, A.K.: Parameter estimation in super-resolution image reconstruction problems. In: Proceedings of the IEEE International Conference on Acoustic, Speech and Signal Processing, China, vol. 3, pp. 709–712 (2003).
120.
Bertero, M., Boccacci, P.: Super-resolution in computational imaging. Micron 34, 265–273 (2003)
121.
Bishop, C., Blake, A., Marthi, B.: Super-resolution enhancement of video. In: Proceedings of Artificial Intelligence and Statistics (2003).
122.
Canel, G., Tekalp, A.M., Heinzelman, W.: Super-resolution recovery for multi-camera surveillance imaging. In: Proceedings of IEEE International Conference on Multimedia and Expo, USA, pp. 109–112 (2003).
123.
Capel, D., Zisserman, A.: Computer vision applied to super-resolution. IEEE Signal Process. Mag. 20(3), 75–86 (2003)
124.
Farsiu, S., Robinson, D., Elad, M., Milanfar, P.: Fast and robust super-resolution. Proceedings of IEEE International Conference on Image Processing, Spain 2, 291–294 (2003)
125.
Farsiu, S., Robinson, D., Elad, M., Milanfar, P.: Robust shift and add approach to super-resolution. In: Proceedings of SPIE Conference on Applications of Digital Signal and Image Processing, USA, pp. 121–130 (2003).
126.
Goldberg, N., Feuer, A., Goodwin, G.C.: Super-resolution reconstruction using spatio-temporal filtering. J. Vis. Commun. Image Represent. 14(4), 508–525 (2003)
127.
Gunturk, B.K., Batur, A.U., Altunbasak, Y., Hayes, M.H., Mersereau, R.M.: Eigenface-domain based super-resolution for face recognition. IEEE Trans. Image Process. 12(5), 597–606 (2003)
128.
Jiang, Z., Wong, T.T., Bao, H.: Practical super-resolution from dynamic video sequences. Proceedings of International Conference on Computer Vision and Pattern Recognition, Canada 2, 549–554 (2003)
129.
Joshi, M.V., Chaudhuri, S.: A learning-based method for image super-resolution from zoomed observations. In: Proceedings of 5th International Conference on Advances in Pattern Recognition, India, pp. 179–182 (2003).
130.
Miravet, C., Rodriguez, F.B.: A hybrid MLP-PNN architecture for fast image super-resolution. In: Proceedings of the International Conference on Neural Information Processing, Turkey, pp. 417–424 (2003).
131.
Ng, M.K., Bose, N.K.: Mathematical analysis of super-resolution methodology. IEEE Signal Process. Mag. 20(3), 62–74 (2003)
132.
Park, S.C., Park, M.K., Kang, M.G.: Super-resolution image reconstruction: a technical overview. IEEE Signal Process. Mag. 20(3), 21–36 (2003)
133.
Pickup, L., Roberts, S., Zisserman, A.: A sampled texture prior for image super-resolution. In: Proceedings of 16th International conference on Advances in Neural Information Processing Systems (2003).
134.
Rajan, D., Chaudhuri, S., Joshi, M.V.: Multi-objective super-resolution: concepts and examples. IEEE Signal Process. Mag. 20(3), 49–61 (2003)
135.
Rajan, D., Chaudhuri, S.: Simultaneous estimation of super-resolved scene and depth map from low resolution observations. IEEE Trans. Pattern Anal. Mach. Intell. 25, 1102–1117 (2003)
136.
Salari, E., Zhang, S.: Integrated recurrent neural network for image resolution enhancement from multiple image frames. IEE Vis. Image Signal Process. 150(5), 299–305 (2003)
137.
Segall, C.A., Molina, R., Katsaggelos, A.K.: High-resolution images from low-resolution compressed video. IEEE Signal Process. Mag. 20(3), 37–48 (2003)
138.
Sun, J., Zheng, N.N., Tao, H., Shum, H.Y.: Image hallucination with primal sketch priors. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition 2, 729–736 (2003)
139.
Tappen, M.F., Russell, B.C., Freeman, W.T.: Exploiting the sparse derivative prior for super-resolution and image demosaicing. In: IEEE Workshop Statistical and Computational Theories of Vision (2003).
140.
Tipping, M.E., Bishop, C.M.: Bayesian image super-resolution. In: Becker, S., Thrun, S., Obermayer, K. (eds.) Advances in Neural Information Processing Systems, vol. 15. MIT Press, USA (2003)
141.
Vandewalle, P., Susstrunk, S.E., Vetterli, M.: Super-resolution images reconstructed from aliased images. Proceedings of SPIE Conference on Visual Communications and Image Processing, Switzerland 5150, 1398–1405 (2003)
142.
Wang, X., Tang, X.: Face hallucination and recognition. In: Proceedings of 4th International Conference on Audio- and Video-based Personal Authentication (IAPR), UK, pp. 486–494 (2003).
143.
Zhao, S., Han, H., Peng, S.: Wavelet-domain HMT-based image super-resolution. Proceedings of IEEE International Conference on Image Processing, Spain 2, 656–953 (2003)
144.
Zweig, G.: Super-resolution Fourier transform by optimization, and ISAR imaging. In: IEE Proceedings on Radar, Sonar and Navigation, pp. 247–252 (2003).
145.
Almansa, A., Durand, S., Rouge, B.: Measuring and improving image resolution by adaptation of the reciprocal cell. J. Math. Imaging Vis. 21, 235–279 (2004)MathSciNet
146.
Begin, I., Ferrie F.P.: Blind super-resolution using a learning-based approach. In: Proceedings of IEEE International Conference on Pattern Recognition, UK, pp. 85–89 (2004).
147.
Ben-Ezra, M., Nayar, S.: Jitter camera: High resolution video from a low resolution detector. Proceeding of IEEE International Conference on Computer Vision and Pattern Recognition, USA 2, 135–142 (2004)
148.
Borman, S.: Topics in multiframe super-resolution restoration. PhD thesis, University of Notre Dame (2004).
149.
Borman, S., Stevenson, R.: Linear models for multi-frame super-resolution restoration under non-affine registration and spatially varying psf. In: SPIE Electronic Imaging (2004).
150.
Bose, N.K., Lertrattanapanich, S., Chappali, M.B.: Super-resolution with second generation wavelets. Signal Process. Image Commun. 19, 387–391 (2004)
151.
Chang, H., Yeung, D.Y., Xiong, Y.: Super-resolution through neighbor embedding. Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, USA 1, 275–282 (2004)
152.
Cristani, M., Cheng, D.S., Murino, V., Pannullo, D.: Distilling information with super-resolution for video surveillance. In: Proceedings of the ACM 2nd International Workshop on Video Surveillance and Sensor Networks, USA (2004).
153.
Cui, J., Wang, Y., Huang, J., Tan, T., Sun, Z.: An iris image synthesis method based on PCA and super-resolution. Proceedings of IEEE International Conference on Pattern Recognition, UK 4, 471–474 (2004)
154.
Dedeoglu, G., Kanade, T., August, J.: High-zoom video hallucination by exploiting spatio-temporal regularities. Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, USA 2, 151–158 (2004)
155.
Farsiu, S., Robinson, D., Elad, M., Milanfar, P.: Advances and challenges in super-resolution. Int. J. Imaging Syst. Technol. 14(2), 47–57 (2004)
156.
Farsiu, S., Robinson, D., Elad, M., Milanfar, P.: Dynamic demosaicing and color super-resolution video sequences. In: Proceedings of SPIE Conference on Image Reconstruction from Incomplete Data (2004).
157.
Farsiu, S., Robinson, D., Elad, M., Milanfar, P.: ’Fast and robust multi-frame super-resolution. IEEE Trans. Image Process. 13(10), 1327–1344 (2004)
158.
Farsiu, S., Elad, M., Milanfar, P.: Multi-frame demosaicing and super-resolution from under-sampled color images. In: Proceedings of SPIE Symposium on Electronic, Imaging, pp. 222–233 (2004).
159.
Gonzalez-Audcana, M., Saleta, J.L., Catalan, R.G., Garcia, R.: Fusion of multispectral and panchromatic images using improved IHS and PCA mergers based on wavelet decomposition. IEEE Trans. Geosci. Remote Sens. 42(6), 1291–1299 (2004)
160.
Gotoh, T., Okutomi, M.: Direct super-resolution and registration using raw CFA images. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA 2, 600–607 (2004)
161.
Gunturk, B.K., Altunbasak, Y., Mersereau, R.M.: Super-resolution reconstruction of compressed video using transform-domain statistics. IEEE Trans. Image Process. 13(1), 33–43 (2004)
162.
Jiji, C.V., Joshi, M.V., Chaudhuri, S.: Single-frame image super-resolution using learned wavelet coefficients. Int. J. Imaging Syst. Technol. 14(3), 105–112 (2004)
163.
Joshi, M.V., Chaudhuri, S., Panuganti, R.: Super-resolution imaging: use of zoom as a cue. Image Vis. Comput. 22, 1185–1196 (2004)
164.
Li, Y., Lin, X.: An improved two-step approach to hallucinating faces. In: Proceedings of 3rd International Conference on Image and Graphics, China, pp. 298–301 (2004).
165.
Li, Y., Lin, X.: Face hallucination with pose variation. In: Proceedings of 6th IEEE International Conference on Automatic Face and Gesture Recognition, Korea, pp. 723–728 (2004).
166.
Lin, Z., Shum, H.Y.: Fundamental limits of reconstruction-based super-resolution algorithms under local translation. IEEE Trans. Pattern Anal. Mach. Intell. 26, 83–97 (2004)
167.
Pham, T.Q., Vliet, L.J.V.: Super-resolution Fusion using adaptive normalized averaging. In: Proceedings of ASCI (2004).
168.
Robinson, D., Milanfar, D.: Statistical performance analysis of super-resolution image reconstruction. In: Proceedings of 38th Asilomar Conference on Signals, Systems and Computers, vol. 1, pp. 144–149 (2004).
169.
Segall, C.A., Katsaggelos, A.K., Molina, R., Mateos, J.: Bayesian resolution enhancement of compressed video. IEEE Trans. Image Process. 13, 898 (2004)
170.
Villena, S., Abad, J., Molina, R., Katsaggelos, A.K.: Estimation of high resolution images and registration parameters from low resolution observations. In: Iberoamerican Congress on Pattern Recognition, Mexico, pp. 509–516 (2004).
171.
Wang, Z., Qi, F.: On ambiguities in super-resolution modeling. IEEE Signal Process. Lett. 11(8), 678–681 (2004)
172.
Wang, C., Wang, R.S.: Super-resolution reconstruction of image sequence using multiple motion estimation fusion. J. Comput. Sci. Technol. 19(3), 405–412 (2004)
173.
Wu, J., Trivedi, M., Rao, B.: Resolution enhancement by AdaBoost. Proceedings of IEEE International Conference on Pattern Recognition, USA 3, 893–896 (2004)
174.
Ahrens, B.: Genetic algorithm optimization of superresolution parameters. In: Proceedings of ACM Conference on Genetic and Evolutionary Computation, USA, pp. 2083–2088 (2005).
175.
Akgun, T., Altunbasak, Y., Mersereau, R.M.: Super-resolution reconstruction of hyperspectral images. IEEE Trans. Image Process. 14, 1860–1875 (2005)
176.
Barreto, D., Alvarez, L., Abad, J.: Motion estimation techniques in super-resolution image reconstruction, a performance evaluation. In: Proceedings of Virtual Observatory: Plate Content Digitization, Archive Mining and Image Sequence Processing, Bulgaria, pp. 254–268 (2005).
177.
Ben-Ezra, M., Zomet, A., Nayar, S.K.: Video super-resolution using controlled subpixel detector shifts. IEEE Trans. Pattern Anal. Mach. Intell. 27(6), 977–987 (2005)
178.
Champagnat, F., Besnerais, G.L.: A Fourier interpretation of super-resolution techniques. Proceedings of IEEE International Conference on Image Processing, Italy 1, 865–868 (2005)
179.
Chappalli, M., Bose, N.: Simultaneous noise filtering and super-resolution with second-generation wavelets. Signal Process. Lett. 12, 772–775 (2005)
180.
Corduneanu, A., Platt, J.C.: Learning spatially-variable filters for super-resolution of text. Proceedings of IEEE International Conference on Image Processing, Italy 1, 849–852 (2005)
181.
Donaldson, K., Myers, D.K.: Bayesian super-resolution of text in video with a text-specific bimodal prior. Int. J. Doc. Anal. Recognit. 7(2), 159–167 (2005)
182.
Farsiu, S.: A fast and robust framework for image fusion and enhancement. PhD thesis, University of California, Santa Cruz (2005).
183.
Farsiu, S., Elad, M., Milanfar, P.: Constrained, globally optimal, multi-frame motion estimation. In: IEEE/SP 13th Workshop on Statistical, Signal Processing, pp. 1396–1401 (2005).
184.
Gevrekci, M., Gunturk, B.K.: Image acquisition modeling for super-resolution reconstruction. IEEE Int. Conf. Image Process. 2, 1058–1061 (2005)
185.
Gupta, M.D., Rajaram, S., Petrovic, N., Huang, T.S.: Non-parametric image super-resolution using multiple images. In: Proceedings of IEEE International Conference on Image Processing, Italy (2005).
186.
He, H., Kondi, L.P.: A regularization framework for joint blur estimation and super-resolution of video sequences. Proceedings of IEEE International Conference on Image Processing, Italy 3, 11–14 (2005)
187.
Jia, K., Gong, S.: Face super-resolution using multiple occluded images of different resolutions. In: Proceedings of IEEE Advanced Video and Signal Based Surveillance, pp. 614–619, Italy (2005).
188.
Jia, K., Gong, S.: Multi-modal face image super-resolutions in tensor space. In: Proceedings of IEEE Advanced Video and Signal Based Surveillance, Italy, pp. 264–269 (2005).
189.
Jia, K., Gong, S.: Multi-modal tensor face for simultaneous super-resolution and recognition. Proceedings of International Conference on Computer Vision, China 2, 1683–1690 (2005)
190.
Lin, F., Fookes, C., Chandran, V., Sridharan, S.: Investigation into optical flow super-resolution for surveillance applications. In: Proceedings of APRS Workshop on Digital Image Computing, Australia, pp. 73–78 (2005).
191.
Lin, D., Liu, W., Tang, X.: Layered local prediction network with dynamic learning for face super-resolution. Proceedings of IEEE International Conference on Image Processing, Italy 1, 885–888 (2005)
192.
Liu, W., Lin, D., Tang, X.: Face hallucination through dual associative learning. Proceedings of IEEE International Conference on Image Processing, Italy 1, 873–876 (2005)
193.
Liu, W., Lin, D., Tang, X.: Hallucinating faces: Tensorpatch super-resolution and coupled residue compensation. Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, USA 2, 478–484 (2005)
194.
Liu, W., Lin, D., Tang, X.: Neighbor combination and transformation for hallucinating faces.In: Proceedings of IEEE International Conference on Multimedia and Expo, The Netherlands (2005).
195.
Mancas-Thillou, C., Mirmehdi, M.: Super-resolution text using the Teager filter. In: Proceedings of 1st International Workshop on Camera-Based Document Analysis and Recognition, Korea, pp. 10–16 (2005).
196.
Miravet, C., Rodrguez, F.B.: Accurate and robust image super-resolution by neural processing of local image representations. Proceedings of International Conference on Artificial Neural Networks, Poland 1, 499–505 (2005)
197.
Ng, M.K., Yau, A.C.: Super-resolution image restoration from blurred low-resolution images. J. Math. Imaging Vis. 23(3), 367–378 (2005)MathSciNet
198.
Papathanassiou, C., Petrou, M.: Super-resolution: an overview. Proceedings of International Symposium on Geoscience and Remote Sensing, Korea 8, 5655–5658 (2005)
199.
Park, J., Kwon, Y., Kim, J.H.: An example-based prior model for text image super-resolution. In: Proceedings of IEEE 8th International Conference on Document Analysis and Recognition, vol. 1, pp. 374–378 (2005).
200.
Peng, S., Pan, G., Wu, Z.: Learning-based super-resolution of 3D face model. Proceedings of IEEE International Conference on Image Processing, Italy 2, 382–385 (2005)
201.
Prendergast, R.S., Nguyen, T.Q.: Improving frequency domain super-resolution via undersampling model. Proceedings of IEEE International Conference on Image Processing, Italy 1, 853–856 (2005)
202.
Roth, S., Black, M.J.: Fields of experts: a framework for learning image priors. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA (2005).
203.
Rubert, C., Fonseca, L., Velho, L.: Learning based super-resolution using YUV model for remote sensing images. In: Proceedings of Workshop of Theses and Dissertations in Computer Graphics and Image Processing (2005).
204.
Sasaharay, R., Hasegawaz, H., Yamaday, I., Sakaniway, K.: A color super-resolution with multiple nonsmooth constraints by hybrid steepest descent method. Proceedings of IEEE International Conference on Image Processing, Italy 1, 857–860 (2005)
205.
Shechtman, E., Caspi, Y., Irani, M.: Space-time super-resolution. IEEE Trans. Pattern Anal. Mach. Intell. 27(4), 531–545 (2005)
206.
Su, C., Huang, L.: Facial expression hallucination. In: Proceedings of 7th IEEE Workshop on Application of Computer Vision, vol. 1, pp. 93–98 (2005).
207.
Su, K., Tian, Q., Que, Q., Sebe, N., Ma, J.: Neighborhood issue in single-frame image super-resolution. In: Proceedings of IEEE International Conference on Multimedia and Expo, The Netherlands (2005).
208.
Su, C., Zhuang, Y., Huang, L., Wu, F.: Steerable pyramid based face hallucination. Pattern Recognit. 38, 813–824 (2005)
209.
Tian, J., Ma, K.K.: A MCMC approach for Bayesian super-resolution image reconstruction. Proceedings of IEEE International Conference on Image Processing, Italy 1, 45–48 (2005)
210.
Tian, J., Ma, K.K.: A new state-space approach for super-resolution image sequence reconstruction. Proceedings of IEEE International Conference on Image Processing, Italy 1, 881–884 (2005)
211.
Vandewalle, P., Sbaiz, L., Vetterli, M., Sustrunk, S.: Super-resolution from highly undersampled images. Proceedings of IEEE International Conference on Image Processing, Italy 1, 889–892 (2005)
212.
Wang, Z., Qi, F.: Analysis of multiframe super-resolution reconstruction for image anti-aliasing and deblurring. Image Vis Comput 23, 393–404 (2005)MATHMathSciNet
213.
Wang, X., Tang, X.: Hallucinating face by eigentransformation. IEEE Trans. Syst. Man Cybern. 35(3), 425–434 (2005)
214.
Wang, Q., Tang, X., Shum, H.: Patch based blind image super-resolution. In: Proceedings of 10th International Conference on Computer Vision, vol. 1, pp. 709–716 (2005).
215.
Woods, N.A., Galatsanos, N.P.: Non-stationary approximate Bayesian super-resolution using a hierarchical prior model. Proceedings of IEEE International Conference on Image Processing, Italy 1, 37–40 (2005)
216.
Ye, G., Pickering, M., Frater, M., Arnold, J.: A robust approach to super-resolution sprite generation. Proceedings of IEEE International Conference on Image Processing, Italy 1, 897–900 (2005)
217.
Zhang, D., Li, H., Du, M.: Fast MAP-based multiframe super-resolution image reconstruction. Image Vis. Comput. 23, 671–679 (2005)
218.
Zibetti, M.V.W., Mayer, J.: Simultaneous super-resolution for video sequences. Proceedings of IEEE International Conference on Image Processing, Italy 1, 877–880 (2005)
219.
Baboulaz, L., Dragotti, P.L.: Distributed acquisition and image super-resolution based on continuous moments from samples. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 3309–3312 (2006).
220.
Begin, I., Ferrie, F.P.: Comparison of super-resolution algorithms using image quality measures. In: Proceedings of 3rd Canadian Conference on Computer and Robot Vision, Canada, p. 72 (2006).
221.
Bose, N.K., Ng, M.K., Yau, A.C.: A fast algorithm for image super-resolution from blurred observations. EURASIP J. Adv. Signal Process. 35726, 14 (2006)
222.
Callic, G.M., Llopis, R.P., Lpez, S., Lopez, J.F., Nunez, A., Sethuraman, R., Sarmiento, R.: Low-cost super-resolution algorithms implementation over a HW/SW video compression platform. EURASIP J. Adv. Signal Process. 84614, 29 (2006)
223.
Choi, B., Ra, J.B.: Region-based super-resolution using multiple blurred and noisy under-sampled images. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Toulouse 2, 609–612 (2006)
224.
Chung, J., Haber, E., Nagy, J.: Numerical methods for coupled super-resolution. Inverse Probl. 22(4), 1261–1272 (2006)MATHMathSciNet
225.
Costa, G.H., Bermudez, J.C.M.: On the design of the LMS algorithm for robustness to outliers in super-resolution video reconstruction. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1737–1740 (2006).
226.
Farsiu, S., Elad, M., Milanfar, P.: A practical approach to super-resolution. In: Proceedings of SPIE: Visual Communications and Image Processing, USA (2006).
227.
Farsiu, S., Elad, M., Milanfar, P.: Multiframe demosaicing and super-resolution of color images. IEEE Trans. Image Process. 15(1), 141–159 (2006)
228.
Farsiu, S., Elad, M., Milanfar, P.: Video-to-video dynamic super-resolution for grayscale and color sequences. EURASIP J. Appl. Signal Process. 61859, 15 (2006)
229.
Gunturk, B.K., Gevrekci, M.: High-resolution image reconstruction from multiple differently exposed images. Signal Process. Lett. 13(4), 197–200 (2006)
230.
He, H., Kondi, L.P.: An image super-resolution algorithm for different error levels per frame. IEEE Trans. Image Process. 15(3), 592–603 (2006)
231.
He, Y., Yap, K.H., Chen, L., Chau, L.P.: Blind super-resolution image reconstruction using a maximum a posteriori estimation. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1729–1732 (2006).
232.
Huang, Y., Long, Y.: Super-resolution using neural networks based on the optimal recovery theory. In: Proceedings of IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing, USA, pp. 465–470 (2006).
233.
Huang, Y., Long, Y.: Super-resolution using neural networks based on the optimal recovery theory. J. Comput. Electron. 5, 275–281 (2006)
234.
Humblot, F., Muhammad-Djafari, A.: Super-resolution using hidden Markov model and Bayesian detection estimation framework. EURASIP J. Adv. Signal Process. 36971, 16 (2006)
235.
Jia, K., Gong, S.: Hallucinating multiple occluded face images of different resolutions. Pattern Recognit. Lett. 27(15), 1768–1775 (2006)
236.
Jia, K., Gong, S.: Multi-resolution patch tensor for facial expression hallucination. In: Proceedings of IEEE International Conference on Pattern Recognition, USA, pp. 395–402 (2006).
237.
Jiji, C.V., Chaudhuri, S.: Single-frame image super-resolution through contourlet learning. EURASIP J. Adv. Signal Process. 73767, 11 (2006)
238.
Joshi, M.V., Chaudhuri, S.: Simultaneous estimation of super-resolved depth map and intensity field using photometric cue. Comput. Vis. Image Underst. 101(1), 31–44 (2006)
239.
Kennedy, J.A., Israel, O., Frenkel, A., Bar-Shalom, R., Azhari, H.: Super-resolution in PET imaging. IEEE Trans. Med. Imaging 25(2), 137–148 (2006)
240.
Kondo, S., Toma, T.: Video coding with super-resolution post-processing. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 3141–3144 (2006).
241.
Kong, D., Han, M., Xu, W., Tao, H., Gong, Y.: A conditional random field model for video super-resolution. In: Proceedings of IEEE International Conference on Pattern Recognition, China (2006).
242.
Kramer, P., Hadar, O., Benois-Pineau, J., Domenger, J.P.: Use of motion information in super-resolution mosaicing. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 357–360 (2006).
243.
Lerotic, M., Yang, G.Z.: The use of super-resolution in robotic assisted minimally invasive surgery. In: Medical Image Computing and Computer-Assisted Intervention, pp. 462–469 (2006).
244.
Li, X.: Super-resolution for synthetic zooming. EURASIP J. Adv. Signal Process. 58195, 12 (2006)
245.
Lian, H.: Variational local structure estimation for image super-resolution. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1721–1724 (2006).
246.
Lv, J., Hao, P.: In-focus imaging by mosaicking and super-resolution. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 2689–2692 (2006).
247.
Molina, R., Vegab, M., Mateos, J., Katsaggelos, A.K.: Parameter estimation in Bayesian reconstruction of multispectral images using super resolution techniques. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1749–1752 (2006).
248.
Mudenagudi, U., Singla, R., Kalra, P., Banerjee, S.: Super-resolution using graph-cut. In: Proceedings of 7th Asian Conference on Computer Vision, India, pp. 385–394 (2006).
249.
Or, S.H., Yu, Y.K., Wong, K.H., Chang, M.M.Y.: Resolution improvement from stereo images with 3d pose differences. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1733–1736 (2006).
250.
Pan, G., Han, S., Wu, Z., Wang, Y. : Super-resolution of 3d face. In: Proceedings of 9th European Conference on Computer Vision, vol. 3952, pp. 389–401 (2006).
251.
Patanavijit, V., Jitapunkul, S.: An iterative super-resolution reconstruction of image sequences using affine block-based registration. In: ACM International Symposium on Multimedia Over Wireless, Canada (2006).
252.
Patanavijit, V., Jitapunkul, S.: An iterative super-resolution reconstruction of image sequences using fast affine block-based registration with BTV regularization. In: Proceedings of IEEE Asia Pacific Conference on Circuits and Systems, pp. 1717–1720 (2006).
253.
Pickup, L.C., Capel, D.P., Roberts, S.J., Zisserman, A.: Bayesian image super-resolution, continued. Neural Inf. Process. Syst. 19, 1089–1096 (2006)
254.
Rajaram, S., Gupta, M.D., Petrovic, N., Huang, T.S.: Learning based nonparametric image super-resolution. EURASIP J. Adv. Signal Process. 51306, 11 (2006)
255.
Reibman, A.R., Bell, R.M., Gray, S.: Quality assessment for super-resolution image enhancement. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 2017–2020 (2006).
256.
Robinson, D., Milanfar, P.: Statistical performance analysis of super-resolution. IEEE Trans. Image Process. 15(6), 1413–1428 (2006)
257.
Sankaran, H.E., Gotchev, A., Egiazarian, K.: Efficient super-resolution reconstruction for translational motion using a near least squares resampling method. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1745–1748 (2006).
258.
Sroubek, F., Flusser, J.: Resolution enhancement via probabilistic deconvolution of multiple degraded images. Pattern Recognit. Lett. 27, 287–293 (2006)
259.
Stephenson, T.A., Chen, T.: Adaptive markov random fields for example-based super-resolution of faces. EURASIP J. Adv. Signal Process. 31062, 11 (2006)
260.
Suresh, K.V., Rajagopalan, A.N.: Super-resolution in the presence of space-variant blur. In: Proceedings of IEEE International Conference on Pattern Recognition, USA, pp. 770–773 (2006).
261.
Takeda, H.: Kernel regression for image processing and reconstruction. PhD thesis, University Of California, Santa Cruz (2006).
262.
Tai, Y.-W., Tong, W.-S., Tang, C.-K.: Perceptually-inspired and edge-directed color image super-resolution. Proceedings of the International Conference on Computer Vision and Pattern Recognition 2, 1948–1955 (2006)
263.
Tuan, P.Q.: Spatiotonal adaptivity in super-resolution of under-sampled image sequences. PhD thesis, Technische Universiteit Delft (2006).
264.
van Eekeren, A.W.M., Schutte, K., Dijk, J., de Lange, D., van Vliet, L.: Super-resolution on moving objects and background. In: Proceedings of the IEEE International Conference on Image Processing, USA, pp. 2709–2712 (2006).
265.
van Ouwerkerk, J.D.: Image super-resolution survey. Image Video Comput. 24(10), 1039–1052 (2006)
266.
Vandewalle, P.: Super-resolution from unregistered aliased images. PhD thesis, Ecole Polytechnique Federale de Lauasnne (2006).
267.
Vandewalle, P., Susstrunk, S., Vetterli, M.: A frequency domain approach to registration of aliased images with application to super-resolution. EURASIP J. Adv. Signal Process. 71459, 14 (2006)
268.
Wang, C., Xue, P., Lin, W.: Improved super-resolution reconstruction from video. IEEE Trans. Circuits Syst. Video Technol. 16(11), 1411–1422 (2006)
269.
Wu, J., Trivedi, M.M.: A regression model in TensorPCA subspace for face image super-resolution reconstruction. In: Proceedings of IEEE International Conference on Pattern Recognition, China (2006).
270.
Yu, J., Bhanu, B.: Super-resolution restoration of facial images in video. In: Proceedings of IEEE 18th International Conference on Pattern Recognition, vol. 4, pp. 342–345 (2006).
271.
Zhang, S.: Application of super-resolution image reconstruction to digital holography. EURASIP J. Adv. Signal Process. 90358, 7 (2006)
272.
Zibetti, M.V.W., Mayer, J.: Outlier robust and edge-preserving simultaneous super-resolution. Proceedings of IEEE International Conference on Image Processing, USA 1, 1741–17441 (2006)
273.
Agrawal, A., Raskar, R.: Resolving objects at higher resolution from a single motion-blurred image. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA (2007).
274.
Baboulaz, L., Dragotti, P.L.: Local feature extraction for image super-resolution. In: Proceedings of IEEE International Conference on Image Processing, USA, p. 401 (2007).
275.
Begin, I., Ferrie, F.P.: PSF recovery from examples for blind super-resolution. Proceedings of IEEE International Conference on Image Processing, USA 5, 421–424 (2007)
276.
Chakrabarti, A., Rajagopalan, A., Chellappa, R.: Super-resolution of face images using kernel-based prior. IEEE Trans. Multimed. 9(4), 888–892 (2007)
277.
Chantas, G.K., Galatsanos, N.P., Woods, N.: Super-resolution based on fast registration and maximum a posteriori reconstruction. IEEE Trans. Image Process. 16(7), 1821–1830 (2007)MathSciNet
278.
Costa, G.H., Bermudez, J.C.M.: Statistical analysis of the LMS algorithm applied to super-resolution image reconstruction. IEEE Trans. Signal Process. 55(5), 2084–2095 (2007)MathSciNet
279.
Dai, S., Han, M., Xu, W., Wu, Y., Gong, Y.: Soft edge smoothness prior for alpha channel super resolution. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, USA (2007).
280.
Dai, S., Han, M., Wu, Y., Gong, Y.: Bilateral back-projection for single image super resolution. In: Proceedings of IEEE International Conference on Multimedia and Expo, USA, pp. 1039–1042 (2007).
281.
Datsenko, D., Elad, M.: Example-based single document image super-resolution: a global map approach with outlier rejection. J. Multidimens. Syst. Signal Process. 2, 103–121 (2007)MathSciNet
282.
Debes, C., Wedi, T., Brown, C.L., Zoubir, A.M.: Motion estimation using a joint optimisation of the motion vector field and a super-resolution reference image. Proceedings of IEEE International Conference on Image Processing, USA 2, 479–500 (2007)
283.
Ebrahimi, M., Vrscay, E.R.: Solving the inverse problem of image zooming using self examples. In: International Conference on Image Analysis and Recognition, pp. 117–130 (2007).
284.
Eekeren, A.W.M.V., Schutte, K., Oudegeest, O.R., van Vliet, L.J.: Performance evaluation of super-resolution reconstruction methods on real-world data. EURASIP J. Adv. Signal Process. 43953, 11 (2007)
285.
Elad, M., Datsenko, D.: Example-based regularization deployed to super-resolution reconstruction of a single image. Comput. J. 18(2), 103–121 (2007)MATHMathSciNet
286.
Fan, W., Yeung, D.Y.: Image hallucination using neighbor embedding over visual primitive manifolds. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA 2, 1–7 (2007)
287.
Fattal, R.: Image upsampling via imposed edge statistics. In: ACM Special Interest Group on Computer Graphics and Interactive Techniques, USA, vol. 26, no. 3, article 95, 8 pages (2007).
288.
Fransens, R., Strecha, C., Gool, L.V.: Optical flow based super-resolution: a probabilistic approach. Comput. Vis. Image Underst. 106(1), 106–115 (2007)
289.
Gevrekci, M., Gunturk, B.K.: Super resolution under photometric diversity of images. EURASIP J. Adv. Signal Process. 36076, 12 (2007)
290.
Hardie, R.C.: A fast image super-resolution algorithm using an adaptive Wiener filter. IEEE Trans. Image Process. 16, 2953–2964 (2007)MathSciNet
291.
He, Y., Yap, K.H., Chen, L., Chau, L.P.: A nonlinear least square technique for simultaneous image registration and super-resolution. IEEE Trans. Image Process. 16(11), 2830–2841 (2007)MathSciNet
292.
Jiji, C.V., Chaudhuri, S., Chatterjee, P.: Single frame image super-resolution: should we process locally or globally? Multidimens. Syst. Signal Process. 18, 123–152 (2007)MATHMathSciNet
293.
Katartzis, A., Petrou, M.: Robust Bayesian estimation and normalized convolution for super-resolution image reconstruction. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA (2007).
294.
Katsaggelos, A.K., Molina, R., Mateos, J.: Super Resolution of Images and Video. Morgan & Claypool Publishers, USA (2007)
295.
Keller, S.H., Lauze, F., Nielsen, M.: Motion compensated video super resolution. In: Sgallari, F., Murli, A., Paragios, N. (eds.) SSVM LNCS, vol. 4485, pp. 801–812 (2007).
296.
Kimura, K., Nagai, T., Nagayoshi, H., Sako, H.: Simultaneous estimation of super-resolved image and 3d information using multiple stereo-pair images. Proceedings of IEEE International Conference on Image Processing, USA 5, 417–420 (2007)
297.
Kopf, J., Cohen, M., Lischinski, D., Uyttendaele, M.: Joint bilateral upsampling. ACM Trans. Graph. 26(3) (2007)
298.
Lin, F., Denman, S., Chandran, V., Sridharan, S.: Automatic tracking, super-resolution and recognition of human faces from surveillance video. In: Proceedings of IAPR Conference on Machine Vision Applications, Japan, pp. 37–40 (2007).
299.
Lin, F., Fookes, C., Chandran, V., Sridharan, S.: Super-resolved faces for improved face recognition from surveillance video. In: Lee, S.W., Li, S.Z. (eds.) ICB. Lecture Notes in Computer Science, vol. 4642, pp. 1–10 (2007).
300.
Lin, Z., He, J., Tang, X., Tang, C.K.: Limits of learning-based superresolution algorithms. In: Proceedings of IEEE International Conference on Computer Vision, Brazil (2007).
301.
Liu, C., Shum, H.Y., Freeman, W.T.: Face hallucination: theory and practice. Int. J. Comput. Vis. 75(1), 115–134 (2007)
302.
Lui, S., Wu, J., Mao, H., Lien, J.J.: Learning-based super-resolution system using single facial image and multi-resolution wavelet synthesis. Proceedings of Asian Conference on Computer Vision, Japan 4884, 96–105 (2007)
303.
Martins, A.L.D., Homem, M.R.P., Mascarenhas, N.D.A.: Super-resolution image reconstruction using the ICM algorithm. Proceedings of IEEE International Conference on Image Processing, USA 4, 205–208 (2007)
304.
Miravet, C., Rodriguez, F.B.: A two step neural network based algorithm for fast image super-resolution. Image Vis. Comput. 25, 1473–1499 (2007)
305.
Mudenagudi, U., Gupta, A., Goel, L., Kushal, A., Kalra, P., Banerjee, S.: Super-resolution of images of 3d scenecs. In: Proceedings of the 8th Asian conference on Computer Vision, Japan, vol. 2, pp. 85–95 (2007).
306.
Narayanan, B., Hardie, R.C., Barner, K.E., Shao, M.: A computationally efficient super-resolution algorithm for video processing using partition filters. IEEE Trans. Circuits Syst. Video Technol. 17(5), 621–634 (2007)
307.
Ng, M.K., Shen, H., Lam, E.Y., Zhang, L.: A total variation regularization based super-resolution reconstruction algorithm for digital video. EURASIP J. Adv. Signal Process. 74585, 16 (2007)
308.
Patanavijit, V., Tae-O-Sot, S., Jitapunkul, S.: A robust iterative super-resolution reconstruction of image sequences using a Lorentzian Bayesian approach with fast affine block-based registration. Proceedings of IEEE International Conference on Image Processing, USA 5, 393–396 (2007)
309.
Patanavijit, V., Jitapunkul, S.: A Lorentzian stochastic estimation for a robust iterative multiframe super-resolution reconstruction with Lorentzian-Tikhonov regularization. EURASIP J. Adv. Signal Process. 34821, 21 (2007)
310.
Park, S.W., Savvides, M.: Breaking the limitation of manifold analysis for super-resolution of facial images. IEEE Int. Conf. Acoust. Speech. Signal Process. 1, 573–576 (2007)
311.
Park, S.W., Savvides, M.: Robust super-resolution of face images by iterative compensating neighborhood relationships. In: Proceedings of the Biometrics Symposium, USA (2007).
312.
Pickup, L.C.: Machine learning in multi-frame image super-resolution. PhD thesis, University of Oxford (2007).
313.
Pickup, L.C., Capel, D.P., Roberts, S.J., Zisserman, A.: Bayesian methods for image super-resolution. Comput. J. 52, 101–113 (2007)
314.
Pickup, L.C., Capel, D.P., Roberts, S.J., Zisserman, A.: Overcoming registration uncertainty in image super-resolution: maximize or marginalize? EURASIP J. Adv. Signal Process. 23565, 14 (2007)
315.
Robinson, D., Farsiu, S., Milanfar, P.: Optimal registration of aliased images using variable projection with applications to super-resolution. Comput. J. 52(1), 31–42 (2007)
316.
Shen, H.F., Zhang, L.P., Huang, B., Li, P.X.: A MAP approach for joint motion estimation, segmentation, and super-resolution. IEEE Trans. Image Process. 16(2), 479–490 (2007)MathSciNet
317.
Suresh, K.V., Rajagopalan, A.N.: Super-resolution using motion and defocus cues. Proceedings of IEEE International Conference on Image Processing, USA 4, 213–216 (2007)
318.
Takeda, H., Farsiu, S., Milanfar, P.: Kernel regression for image processing and reconstruction. IEEE Trans. Image Process. 16(2), 349–366 (2007)MathSciNet
319.
Thillou, C.M., Mirmehdi, M.: An introduction to super-resolution text. Adv. Pattern Recognit. 305–327 (2007)
320.
Tong, C.S., Leung, K.T.: Super-resolution reconstruction based on linear interpolation of wavelet coefficients. Multidimens. Syst. Signal Process. 18, 153–171 (2007)MATHMathSciNet
321.
Vandewalle, P., Sbaiz, L., Vandewalle, J., Vetterli, M.: Super-resolution from unregistered and totally aliased signals using subspace methods. IEEE Trans. Image Process. 55(7), 3687–3703 (2007)
322.
Wheeler, F., Liu, X., Tu, P.: Multi-Frame Super-Resolution for Face Recognition. In: Proceeding of IEEE Conference on Biometrics: Theory, Applications and Systems, USA, pp. 27–29 (2007).
323.
Yan, H., Liu, J., Sun, J., Sun, X.: ICA based super-resolution face hallucination and recognition. In: Proceedings of the 4th International Symposium on Neural Networks, vol. 2, pp. 1065–1071 (2007).
324.
Yang, Q.X., Yang, R.G., Davis, J., Nister, D.: Spatial-depth super resolution for range images. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA (2007)
325.
Yao, Y., Abidi, B., Kalka, N.D., Schimid, N., Adibi, M.: Super-resolution for high magnification face images. In: Proceedings of the SPIE Defense and Security Symposium, Biometric Technology for Human Identification (2007).
326.
Yu, J., Bhanu, B., Xu, Y., Roy-Chowdhury, A.K.: Super-resolved facial texture under changing pose and illumination. Proceedings of IEEE International Conference on Image Processing, USA 3, 553–556 (2007)
327.
Zhang, S.T., Lu, Y.H.: Image resolution enhancement using a Hopfield neural network. In: Proceedings of IEEE International Conference on Information Technology: New Generations (2007).
328.
Zhuang, Y., Zhang, J., Wu, F.: Hallucinating faces: LPH super-resolution and neighbor reconstruction for residue compensation. Pattern Recognit. 40(11), 3178–3194 (2007)MATH
329.
Zibetti, M.V.W., Mayer, J.: A robust and computationally efficient simultaneous super-resolution scheme for image sequences. IEEE Trans. Circuits Syst. Video Technol. 17(10), 1288–1300 (2007)
330.
Ahmed, S., Rao, N.I., Ghafoor, A., Sheri, A.M.: Direct hallucination: direct locality preserving projections (DLPP) for face super-resolution. In: Proceedings of IEEE International Conference on Advanced Computer Theory and Engineering, Thailand, pp. 105–110 (2008).
331.
Akgun, T.: Resolution enhancement using image statistics and multiple aliased observations. PhD thesis, Georgia Institute of Technology (2008).
332.
Babacan, S.D., Molina, R., Katsaggelos, A.K.: Total variation super resolution using a variational approach. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 641–644 (2008).
333.
Brandi, F., de Queiroz, R.L., Mukherjee, D.: Super-resolution of video using key frames and motion estimation. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 321–324 (2008).
334.
Callico, G.M., Lopez, S., Sosa, O., Lopez, J.F., Sarmiento, R.: Analysis of fast block matching motion estimation algorithms for video super-resolution systems. IEEE Trans. Consum. Electron. 54(3), 1430–1438 (2008)
335.
Costa, G.H., Bermudez, J.C.M.: Informed choice of the LMS parameters in super-resolution video reconstruction applications. IEEE Trans. Signal Process. 56(2), 555–564 (2008)MathSciNet
336.
Cristobal, G., Gil, E., Sroubek, F., Flusser, J., Miravet, C., Rodrguez, F.B.: Superresolution imaging: a survey of current techniques. In: Advanced Signal Processing Algorithms, Architectures, and Implementations, vol. XVIII, pp. 70740C–70740C18 (2008).
337.
Eekeren, A.W.M.V., Schutte, K., Vliet, L.J.V.: Super-resolution on small moving objects. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1248–1251 (2008).
338.
El-Yamany, N.A., Papamichalis, P.E.: Using bounded-influence m-estimators in multi-frame super-resolution reconstruction: a comparative study. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 337–340 (2008).
339.
Hennings-Yeomans, P.H., Baker, S., Kumar, B.: Recognition of low-resolution faces using multiple still images and multiple cameras. In: IEEE International Conference on Biometrics: Theory, Applications and Systems, USA, pp. 1–6 (2008).
340.
Hennings-Yeomans, P.H., Baker, S., Kumar, B.: Simultaneous super-resolution and feature extraction for recognition of low-resolution faces. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA (2008).
341.
Jia, K., Gong, S.: Generalized face super-resolution. IEEE Trans. Image Process. 17(6), 873–886 (2008)MathSciNet
342.
Jiang, F., Wang, Y.: Facial aging simulation based on super-resolution in tensor space. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1648–1651 (2008).
343.
Kim, K.I., Kwon, Y.: Example-based learning for single-image super-resolution. In: Proceedings of the DAGM symposium on Pattern Recognition, Germany (2008).
344.
Kumar, B.G.V., Aravind, R.: Face hallucination using OLPP and kernel ridge regression. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 353–356 (2008).
345.
Li, B., Chang, H., Shan, S., Chen, X., Gao, W.: Hallucinating facial images and features. In: Proceedings of IEEE International Conference on Pattern Recognition, USA (2008).
346.
Li, F., Jia, X., Fraser, D.: Universal HMT based super resolution for remote sensing images. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 333–336 (2008).
347.
Li, F., Yu, J., Chai, J.: A hybrid camera for motion deblurring and depth map super-resolution. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA (2008).
348.
Li, L., Wang, Y.D.: Face super-resolution using a hybrid model. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1153–1157 (2008).
349.
Lin, Z., He, J., Tang, X., Tang, C.K.: Limits of learning-based super-resolution algorithms. Int. J. Comput. Vis. 80(3), 406–420 (2008)
350.
Liu, J., Qiao, J., Wang, X., Li, Y.: Face hallucination based on independent component analysis. In: Proceedings of IEEE International Symposium on Circuits and Systems, USA, pp. 3242–3245 (2008).
351.
Liu, H.Y., Zhang, Y.S., Ji, S.: Study on the methods of super-resolution image reconstruction. In: Proceedings of International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, China, vol. XXXVII, no. B2 (2008).
352.
Malczewski, K., Stasinski, R.: Toeplitz-based iterative image fusion scheme for MRI. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 341–344 (2008).
353.
Molina, R., Vega, M., Mateos, J., Katsaggelos, A.: Variational posterior distribution approximation in Bayesian super-resolution reconstruction of multispectral images. Appl. Comput. Harmon. Anal. 24(2), 251–267 (2008)MATHMathSciNet
354.
Marquina, A., Osher, S.: Image super-resolution by TV-regularization and Bregman iteration. J. Sci. Comput. 37(3), 367–382 (2008)MATHMathSciNet
355.
Pan, G., Han, S., Wu, Z.: Hallucinating 3D facial shapes. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA (2008).
356.
Park, J.S., Lee, S.W.: An example-based face hallucination method for single-frame, low-resolution facial images. IEEE Trans. Image Process. 17(10), 1806–1816 (2008)MathSciNet
357.
Patil, V.H., Bormane, D.S., Pawar, V.S.: Super-resolution using neural network. In: Proceedings of IEEE 2nd Asia International Conference on Modeling and Simulation, Malaysia (2008).
358.
Peyre, G., Bougleux, S., Cohen, L.: Non-local regularization of inverse problems. In: Proceeding of European Conference on Computer Vision, France (2008).
359.
Prendergast, R.S., Nguyen, T.Q.: A block-based super-resolution for video sequences. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1240–1243 (2008).
360.
Robinson, M.D., Farsiu, S., Lo, J.Y., Toth, C.A.: Efficient restoration and enhancement of super-resolved X-ray images. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 629–632 (2008).
361.
Sanguansat, P.: Face hallucination using bilateral-projection-based two-dimensional principal component analysis. In: Proceedings of IEEE International Conference on Computer and Electrical Engineering, Thailand, pp. 876–880 (2008).
362.
Shan, Q., Li, Z., Jia, J., Tang, C.K.: Fast image/video upsampling. In: Proceedings of ACM Annual Conference Series SIGGRAPH, Computer Graphics, USA (2008).
363.
Shao, W.Z., Wei, Z.H.: Edge-and-corner preserving regularization for image interpolation and reconstruction. Image Vis. Comput. 26, 1591–1606 (2008)
364.
Shimizu, M., Yoshimura, S., Tanaka, M., Okutomi, M.: Super-resolution from image sequence under influence of hot-air optical turbulence. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA (2008).
365.
Simonyan, K., Grishin, S., Vatolin, D., Popov, D.: Fast video super-resolution via classification. In: Proceedings of IEEE International Conference on Image Processing, USA, pp 349–352 (2008).
366.
Sroubek, F., Cristobal, G., Flusser, J.: Simultaneous super-resolution and blind deconvolution. J. Phys. Conf. Ser. 124, 1–8 (2008)
367.
Su, H., Tang, L., Tretter, D., Zhou, J.: A practical and adaptive framework for super-resolution. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1236–1239 (2008).
368.
Sun, J., Sun, J., Xx, Z.B., Shum, H.Y.: Image super-resolution using gradient profile prior. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, USA (2008).
369.
Tanaka, M., Yaguchi, Y., Okutomi, M.: Robust and accurate estimation of multiple motions for whole-image super-resolution. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 649–652 (2008).
370.
Takeshima, H., Kaneko, T.: Image registration using subpixel-shifted images for super-resolution. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 2404–2407 (2008).
371.
Vandewalle, P., Baboulaz, L., Dragotti, P.L., Vetterli, M.: Subspace-based methods for image registration and super-resolution. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 645–648 (2008).
372.
Wang, Y., Fevig, R., Schultz, R.R.: Super-resolution mosaicking of UAV surveillance video. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 345–348 (2008).
373.
Wang, X., Liu, J., Qiao, J., Chu, J., Li, Y.: Face hallucination based on CSGT and PCA. In: Advances in Neural Networks. Lecture Notes in Computer Science, vol. 5264, pp. 410–418 (2008).
374.
Wang, Z., Miao, Z.: Feature-based super-resolution for face recognition. In: Proceedings of IEEE International Conference on Multimedia and Expo, Germany, pp. 1569–1572 (2008).
375.
Wang, Z., Miao, Z., Zhang, C.: Extraction of high-resolution face image from low-resolution and variant illumination video Sequences. In: Proceedings of International Congress on Image and Signal Processing, China (2008).
376.
Xiao, C.B., Jing, Y., Yi, X.: A high-efficiency super-resolution reconstruction algorithm from image/video sequences. In: Proceedings of IEEE International Conference on Signal-Image Technologies and Internet-based System, China, pp. 573–580 (2008).
377.
Xiong, Z., Sun, X., Wu, F.: Super-resolution for low quality thumbnail images. In: Proceedings of IEEE International Conference on Multimediam and Expo, Germany, pp. 181–184 (2008).
378.
Yamany, N.A., Papamichalis, P.E.: Robust color image super-resolution: an adaptive M-estimation framework. EURASIP J. Image Video Process. 763254, 12 (2008)
379.
Yang, H., Gao, J., Wu, Z.: Blur identification and image super-resolution reconstruction using an approach similar to variable projection. IEEE Signal Process. Lett. 15, 289–292 (2008)
380.
Yang, J., Tang, H., Ma, Y., Huang, T.: Face hallucination via sparse coding. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1264–1267 (2008).
381.
Yang, J., Wright, J., Huang, T., Ma, Y.: Image super-resolution as sparse representation of raw image patches. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, USA (2008).
382.
Yu, J., Bhanu, B.: Super-resolution of deformed facial images in video. In: Proceedings of IEEE International Conference on Image Processing, USA, pp. 1160–1163 (2008).
383.
Zhang, X., Peng, S., Jiang, J.: An adaptive learning method for face hallucination using locality preserving projections. In: Proceedings of IEEE International Conference on Automatic Face and Gesture Recognition, The Netherlands (2008).
384.
Baboulaz, L., Dragotti, P.: Exact feature extraction using finite rate of innovation principles with an application to image super-resolution. IEEE Trans. Image Process. 18(2), 281–298 (2009).
385.
Belekos, S.P., Galatsanos, N.P., Babacan, S.D., Katsaggelos, A.K.: Maximum a posteriori super-resolution of compressed video using a new multichannel image prior. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 2797–2800 (2009).
386.
Carcenac, M.: A modular neural network for super-resolution of human faces. Appl. Intell. 30(2), 168–186 (2009)
387.
Chan, T.M., Zhang, J.P., Pu, J., Huang, H.: Neighbor embedding based super-resolution algorithm through edge detection and feature selection. Pattern Recognit. Lett. 30, 494–502 (2009)
388.
Costa, G.H., Bermudez, J.: Registration errors: are they always bad for super-resolution? IEEE Trans. Signal Process. 57(10), 3815–3826 (2009)MathSciNet
389.
Edeler, T., Ohliger, K., Hussmann, S., Mertins, A.: Super resolution of time-of-flight depth images under consideration of spatially varying noise variance. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 1185–1188 (2009).
390.
Eekeren, A.W.M.V.: Super-resolution of moving objects in under-sampled image sequences. PhD thesis, Technische Universiteit Delft (2009).
391.
Fan, N.: Super-resolution using regularized orthogonal matching Pursuit based on compressed sensing theory in the wavelet domain. In: Proceedings of International Conference on Computer Graphics, Imaging and Visualization, China, pp. 349–354 (2009).
392.
Glasner, D., Bagon, S., Irani, M.: Super-resolution from a single image. In: Proceedings of IEEE International Conference on Computer Vision, Japan (2009).
393.
Ginesu, G., Dess, T., Atzori, L., Giusto, D.D.: Super-resolution reconstruction of video sequences based on back-projection and motion estimation. In: Proceedings of International Conference on Mobile Multimedia Communications, UK (2009).
394.
Guo, K., Yang, X., Zhang, R., Yu, S.: Learning super resolution with global and local constraints. In: Proceedings of IEEE International Conference on Multimedia and Expo, USA, pp. 590–593 (2009).
395.
Han, C.C., Tasi, Y.S., Hsieh, C.T., Chou, C.H.: The interpolation of face/license-plate images using pyramid-based hallucination. In: Proceedings of International Carnahan Conference on Security Technology, Switzerland (2009).
396.
He, Y., Yap, K.-H., Chen, L., Chau, L.-P.: A soft MAP framework for blind super-resolution image reconstruction. Image Vis. Comput. 27, 364–373 (2009)
397.
Hsu, C.C., Lin, C.W., Hsu, C.T., Liao, H.Y.M.: Cooperative face hallucination using multiple references. In: Proceedings of IEEE International Conference on Multimedia and Expo, USA (2009).
398.
Hung, K.W., Siu, W.C.: New motion compensation model via frequency classification for fast video super-resolution. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 1193–1196 (2009).
399.
Ito, S., Yamada, Y.: Improvement of spatial resolution in magnetic resonance imaging using quadratic phase modulation. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 2497–2500 (2009).
400.
Ji, H., Fermuller, C.: Robust wavelet-based super-resolution reconstruction: theory and algorithm. IEEE Trans. Pattern Anal. Mach. Intell. 31(4), 649–660 (2009)
401.
Jun, Z., Xia, D., Tiangang, D.: A non-linear warping method for face hallucination based-on subdivision mesh. In: Proceedings of IEEE International Congress on Image and Signal Processing, China (2009).
402.
Jung, M., Marquina, A., Vese, L.A.: Multiframe image restoration in the presence of noisy blur kernel. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 1529–1532 (2009).
403.
Kim, C., Choi, K., Beom Ra, J.: Improvement on learning-based super-resolution by adopting residual information and patch reliability. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 1197–1200 (2009).
404.
Li, B., Chang, H.: Aligning coupled manifolds for face hallucination. IEEE Signal Process. Lett. 16(11), 957–960 (2009)
405.
Li, B., Chang, H., Shan, S., Chen, X.: Locality preserving constraints for super-resolution with neighbor embedding. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 1189–1192 (2009).
406.
Li, X., Lam, K.M., Qiu, G., Shen, L., Wang, S.: Example-based image super-resolution with class-specific predictors. J. Vis. Commun. Image Represent. 20(5), 312–322 (2009)
407.
Dai, S., Han, M., Xu, W., Wu, Y., Gong, Y., Katsaggelos, A.K.: SoftCuts: a soft edge smoothness prior for color image super-resolution. IEEE Trans. Image Process. 18(5), 969–981 (2009)MathSciNet
408.
Hu, Y., Shen, T., Lam, K.M.: Region-based Eigentransformation for face image hallucination. In: Proceedings of IEEE International Symposium on Circuits and Systems, Taiwan, pp. 1421–1424 (2009).
409.
Krylov, A.S., Lukin, A.S., Nasonov, A.V.: Edge-preserving nonlinear iterative image resampling method. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 385–388 (2009).
410.
Liang, Y., Lai, J.H., Zou, Y.X., Zheng, W.S., Yuen, P.C.: Face hallucination through KPCA. In: Proceedings of IEEE International Congress on Image and Signal Processing, China (2009).
411.
Ma, Y.J., Zhang, H., Xue, Y., Zhang, S.: Super-resolution image reconstruction based on K-means-Markov network. Proceedings of IEEE International Conference on Natural Computation, China 1, 316–318 (2009)
412.
Ma, X., Zhang, J., Qi, C.: Hallucinating faces: global linear modal based super-resolution and position based residue compensation. In: Image Analysis and Processing. Lecture Notes in Computer Science, vol. 5716, pp. 835–843 (2009).
413.
Ma, X., Zhang, J., Qi, C.: An example-based two-step face hallucination method through coefficient learning. In: Image Analysis and Recognition. Lecture Notes in Computer Science, vol. 5627, pp. 471–480 (2009).
414.
Ma, X., Zhang, J., Qi, C.: Position-based face hallucination method. In: Proceedings of IEEE International Conference on Multimedia and Expo, USA, pp. 290–293 (2009).
415.
Mitzel, D., Pock, T., Schoenemann, T., Cremers, D.: Video super- resolution using duality based TV-L1 optical flow. In: DAGM-Symposium, pp. 432–441, (2009).
416.
Orieux, F., Rodet, T., Giovannelli, J.-F.: Super-resolution with continuous scan shift. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 1169–1172 (2009).
417.
Patanavijit, V.: Super-resolution reconstruction and its future research direction. AU J. 12(3), 149–163 (2009)
418.
Patel, D., Chaudhuri, S.: Performance analysis for image super-resolution using blur as a cue. In: Proceedings of IEEE International Conference on Advances in Pattern Recognition, India, pp. 73–76 (2009).
419.
Protter, M., Elad, M.: Super-resolution with probabilistic motion estimation. IEEE Trans. Image Process. 18(8), 1899–1904 (2009)MathSciNet
420.
Protter, M., Elad, M., Takeda, H., Milanfar, P.: Generalizing the nonlocal-means to super-resolution reconstruction. IEEE Trans. Image Process. 18(1), 36–51 (2009)MathSciNet
421.
Sankur, B., Ozdemir, H.: Subjective evaluation of single frame super-resolution algorithms. In: Proceedings of European Signal Processing Conference, Scotland (2009).
422.
Schuon, S., Theobalt, C., Davis, J., Thrun, S.: LidarBoost: depth superresolution for ToF 3D shape scanning. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA, pp. 343–350 (2009).
423.
Seong, Y.M., Park, H.: A high-resolution image reconstruction method from low-resolution image sequence. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 1181–1184 (2009).
424.
Sen, P., Darabi, S.: Compressive image super-resolution. In: Proceedings of 43rd IEEE Asilomar Conference on Signals, Systems and Computers, USA, pp. 1235–1242 (2009).
425.
Shao, M., Wang, Y., Wang, Y.: A super-resolution based method to synthesize visual images from near infrared. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 2453–2456 (2009).
426.
Shen, H., Li, S.: Hallucinating faces by interpolation and principal component analysis. In: Proceedings of International Symposium on Computational Intelligence and Design, China, pp. 295–298 (2009).
427.
Takeda, H., Milanfar, P., Protter, M., Elad, M.: Super-resolution without explicit subpixel motion estimation. IEEE Trans. Image Process. 18(9), 1958–1975 (2009)MathSciNet
428.
Tian, J., Ma, K.-K.: A state-space super-resolution approach for video reconstruction. Signal Image Video Process. 3(3), 217–240 (2009)MATHMathSciNet
429.
Turgay, E., Akar, G.B.: Directionally adaptive super-resolution. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 1201–1204 (2009).
430.
Wang, Q., Song, X.: Joint image registration and super-resolution reconstruction based on regularized total least norm. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 1537–1540 (2009).
431.
Xiong, Z., Sun, X., Wu, F.: Web cartoon video hallucination. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 3941–3944 (2009).
432.
Yang, J., Schonfeld, D.: New results on performance analysis of super-resolution image reconstruction. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 1517–1520 (2009).
433.
Yap, K.H., He, Y., Tian, Y., Chau, L.P.: A nonlinear l1-norm approach for joint image registration and super-resolution. IEEE Signal Process. Lett. 16(11), 981–984 (2009)
434.
Yeomans, P.H.H., Kumar, B.V.K.V., Baker, S.: Robust low-resolution face identification and verification using high-resolution features. In: Proceedings of IEEE International Conference on Image Processing, Egypt, pp. 33–36 (2009).
435.
Zhao, H., Lu, Y., Zhai, Z.: Example-based facial sketch hallucination. In: Proceedings of International Conference on Computational Intelligence and Security, China, pp. 578–582 (2009).
436.
Zhao, H., Lu, Y., Zhai, Z., Yang, G.: Example-based regularization deployed to face hallucination. Proceedings of International Conference on Computer Engineering and Technology, Singapore 1, 485–489 (2009)MATH
437.
Adler, A., Hel-Or, Y., Elad, M.: A shrinkage learning approach for single image super-resolution with overcomplete representations. Proceedings of European Conference on Computer Vision, Greece 2, 622–635 (2010)
438.
Amro, I., Mateos, J., Vega, M.: Bayesian super-resolution pansharpening using contourlets. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 809–812 (2010).
439.
Anantrasirichai, N., Canagarajah, C.N.: Spatiotemporal super-resolution for lowbitrate H.264 video. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2809–2812 (2010).
440.
Basavaraja, S.V., Bopardikar, A.S., Velusamy, S.: Detail warping based video super-resolution using image guides. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2009–2012 (2010).
441.
Belekos, S.P., Galatsanos, N.P., Katsaggelos, A.K.: Maximum a posteriori video super-resolution using a new multichannel image prior. IEEE Trans. Image Process. 19(6), 1451–1464 (2010)MathSciNet
442.
Bhushan, D.B., Sowmya, V., Soman, K.P.: Super-resolution blind reconstruction of low resolution images using framelets based fusion. In: Proceedings of International Conference on Recent Trends in Information, Telecommunication and Computing, India, pp. 100–104 (2010).
443.
Boonim, K., Sanguansat, P.: Error estimation by regression model and Eigentransformation for face hallucination. In: Proceedings of International Conference on Pervasive Computing Signal Processing and Applications, China, pp. 873–878 (2010).
444.
Boonim, K., Sanguansat, P.: The color face hallucination using Eigentransformation with error regression model. In: Proceedings of International Symposium on Communications and Information Technologies, China, pp. 424–429 (2010).
445.
Cohen, Y.H., Fattal, R., Lischinski, D.: Image upsampling via texture hallucination. In: Proceedings of IEEE International Conference on Computational Photography, USA (2010).
446.
Eekeren, A.W.M.V., Schutte, K., Vliet, L.J.V.: Multiframe super-resolution reconstruction of small moving objects. IEEE Trans. Image Process. 19(11), 2901–2912 (2010)MathSciNet
447.
Faramarzi, E., Bhakta, V.R., Rajan, D., Christensen, M.P.: Super resolution results in panoptes, an adaptive multi-aperture folded architecture. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2833–2836 (2010).
448.
Gajjar, P.P., Joshi, M.V.: New learning based super-resolution: use of DWT and IGMRF prior. IEEE Trans. Image Process. 19(5), 1201–1213 (2010)MathSciNet
449.
Gajjar, P.P., Joshi, M.: Zoom based super-resolution: a fast approach using particle swarm optimization. In: Image and Signal Processing. Lecture Notes in Computer Science, vol. 6134, pp. 63–70 (2010).
450.
Garcia, D.C., Dorea, C., de Queiroz, R.L.: Super-resolution for multiview images using depth information. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 1793–1796 (2010).
451.
Gholipour, A., Estroff, J.A., Warfield, S.K.: Robust super-resolution volume reconstruction from slice acquisitions: application to fetal brain MRI. IEEE Trans. Med. Imaging 29(10), 1739–1758 (2010)
452.
Giachetti, A.: Irradiance preserving image interpolation. In: Proceedings of International Conference on Pattern Recognition, Turkey, pp. 2218–2221 (2010).
453.
Han, F., Fang, X., Wang, C.: Blind super-resolution for single image reconstruction. In: Proceedings of Pacific-Rim Symposium on Image and Video Technology, Singapore, pp. 399–403 (2010).
454.
Han, H., Shan, S., Chen, X., Gao, W.: Gray-scale super-resolution for face recognition from low grayscale resolution face images. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2825–2828 (2010).
455.
Harmeling, S., Sra, S., Hirsch, M., Scholkopf, B.: Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 3313–3317 (2010).
456.
Hsu, C.C., Lin, C.W., Hsu, C.T., Liao, H.Y.M., Yu, J.Y.: Face hallucination using Bayesian global estimation and local basis selection. In: Proceedings of IEEE International Workshop on Multimedia Signal Processing, France, pp. 449–453 (2010).
457.
Hu, Y., Lam, K.M., Qiu, G., Shen, T., Tian, H.: Learning local pixel structure for face hallucination. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2797–2800 (2010).
458.
Huang, H., Wu, N., Fan, X., Qi, C.: Face image super resolution by linear transformation. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 913–916 (2010).
459.
Huanga, H., Hea, H., Fanb, X., Zhang, J.: Super-resolution of human face image using canonical correlation analysis. Pattern Recognit. 43(7), 2532–2343 (2010)
460.
Iiyama, M., Kakusho, K., Minoh, M.: Super-resolution texture mapping from multiple view images. In: Proceedings of International Conference on Pattern Recognition, Turkey, pp. 1820–1823 (2010).
461.
Islam, M.M., Asari, V.K., Islam, M.N., Karim, M.A.: Super-resolution enhancement technique for low resolution video. IEEE Trans. Consum. Electron. 56(2), 919–924 (2010)
462.
Kang, Q.: Patch-based face hallucination with locality preserving projection. In: Proceedings of International Conference on Genetic and Evolutionary Computing, China, pp. 394–397 (2010).
463.
Kim, C., Choi, K., Lee, H., Hwang, K., Ra, J.B.: Robust learning-based super-resolution. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2017–2020 (2010).
464.
Kim, M., Ku, B., Chung, D., Shin, H., Kang, B., Han, D.K., Ko, H.: Robust dynamic super resolution under inaccurate motion estimation. In: Proceedings of IEEE International Conference on Advanced Video and Signal Based Surveillance, USA, pp. 323–328 (2010).
465.
Kim, K.I., Kwon, Y.: Single-image super-resolution using sparse regression and natural image prior. IEEE Trans. Pattern Anal. Mach. Intell. 32(6), 1127–1133 (2010)MathSciNet
466.
Kumar, B.G.V., Aravind, R.: Computationally efficient algorithm for face super-resolution using (2D)2-PCA based prior. IET Image Process. 4(2), 61–69 (2010)MathSciNet
467.
Kumar, S., Nguyen, T.Q.: Total subset variation prior. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 77–80 (2010).
468.
Lan, C., Hu, R., Han, Z., Wang, Z.: A face super-resolution approach using shape semantic mode regularization. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2021–2024 (2010).
469.
Lee, I.H., Bose, N.K., Lin, C.W.: Locally adaptive regularized super-resolution on video with arbitrary motion. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 897–900 (2010).
470.
Li, B., Chang, H., Shan, S.: Low-resolution face recognition via coupled locality preserving mappings. IEEE Signal Process. Lett. 17(1), 20–23 (2010)
471.
Li, Y.R., Dai, D.Q., Shen, L.: Multiframe super-resolution reconstruction using sparse directional regularization. IEEE Trans. Circuits Syst. Video Technol. 20(7), 945–956 (2010)MathSciNet
472.
Li, X., Hu, Y., Gao, X., Tao, D.: A multi-frame image super-resolution method. Signal Process. 90(2), 405–414 (2010)MATH
473.
Liang, Y., Lai, J.H., Xie, X., Liu, W.: Face hallucination under an image decomposition perspective. In: Proceedings of International Conference on Pattern Recognition, Turkey, pp. 2158–2161 (2010).
474.
Liu, S., Brown, M.S., Kim, S.J., Tai, Y.W.: Colorization for single image super resolution. Proceedings of European Conference on Computer Vision, Greece 4, 323–336 (2010)
475.
Ma, X., Huang, H., Wang, S., Qi, C.: A simple approach to multiview face hallucination. IEEE Signal Process. Lett. 17(6), 579–582 (2010)
476.
Maa, X., Zhang, J., Qi, C.: Hallucinating face by position-patch. Pattern Recognit. 43, 2224–2236 (2010)
477.
Mallat, S., Yu, G.: Super-resolution with sparse mixing estimators. IEEE Trans. Image Process. 19(11), 2889–2900 (2010)MathSciNet
478.
Miraveta, C., Rodrigueza, F.B.: A PCA-based super-resolution algorithm for short image sequences. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2025–2028 (2010).
479.
Mochizuki, Y., Kameda, Y., Imiya, A., Sakai, T., Imaizumi, T.: An iterative method for superresolution of optical flow derived by energy minimisation. In: Proceedings of International Conference on Pattern Recognition, Turkey, pp. 2270–2273 (2010).
480.
Nasonov, A.V., Krylov, A.S.: Fast super-resolution using weighted median filtering. In: Proceedings of International Conference on Pattern Recognition, Turkey, pp. 2230–2233 (2010).
481.
Nasrollahi, K., Moeslund, T.B.: Finding and improving the key-frames of long video sequences for face recognition. In: Proceedings of IEEE Conference on Biometrics: Theory, Applications and System, USA (2010).
482.
Nasrollahi, K., Moeslund, T.B.: Hallucination of super-resolved face images. In: Proceedings of IEEE 10th International Conference on Signal Processing, China (2010).
483.
Nasrollahi, K., Moeslund, T.B.: Hybrid super-resolution using refined face-logs. In: Proceedings of IEEE 2nd International Conference on Image Processing Theory, Tools and Applications, France (2010).
484.
Nguyen, C.D., Ardabilian, M., Chen, L.: Unifying approach for fast license plate localization and super-resolution. In: Proceedings of International Conference on Pattern Recognition, Turkey, pp. 376–380 (2010).
485.
Omer, O.A., Tanaka, T.: Image superresolution based on locally adaptive mixed-norm. J. Electr. Comput. Eng. 2010(435194), 4 (2010)
486.
Ozcelikkale, A., Akar, G.B., Ozaktas, H.M.: Super-resolution using multiple quantized images. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2029–2032 (2010).
487.
Pan, Q., Gao, C., Liu, N.: Single frame image super-resolution based on sparse geometric similarity. J. Inf. Comput. Sci. 7(3), 799–805 (2010)
488.
Robinson, M.D., Toth, C.A., Lo, J.Y., Farsiu, S.: Efficient Fourier-wavelet super-resolution. IEEE Trans. Image Process. 19(10), 2669–2681 (2010)MathSciNet
489.
Rousseau, F.: A non-local approach for image super-resolution using intermodality priors. Med. Image Anal. 14, 594–605 (2010)
490.
Sadaka, N.G., Karam, L.J.: Super-resolution using a wavelet-based adaptive wiener filter. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 3309–3312 (2010).
491.
Song, H., Zhang, L., Wang, P., Zhang, K., Li, X.: An adaptive L1–L2 hybrid error model to super-resolution. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2821–2824 (2010).
492.
Shen, M., Wang, C., Xue, P., Lin, W.: Performance of reconstruction-based super-resolution with regularization. J. Vis. Commun. Image Represent. 21, 640–650 (2010)
493.
Shen, M., Xue, P.: Low-power video acquisition with super-resolution reconstruction for mobile devices. IEEE Trans. Consum. Electron. 56(4), 2520–2529 (2010)
494.
Sun, J., Zhu, J.J., Tappen, M.F.: Context-constrained hallucination for image super-resolution. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA (2010).
495.
Tai, Y.W., Liu, S., Brown, M.S., Lin, S.: Super resolution using edge prior and single image detail synthesis. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA, pp. 2400–2407 (2010).
496.
Tanveer, M., Iqbal, N.: A Bayesian approach to face hallucination using DLPP and KRR. In: Proceedings of International Conference on Pattern Recognition, Turkey, pp. 2154–2157 (2010).
497.
Tian, J., Ma, K.K.: Stochastic super-resolution image reconstruction. J. Vis. Commun. Image Represent. 21(3), 232–244 (2010)
498.
Tian, L., Suzuki, A., Koike, H.: Task-oriented evaluation of super-resolution techniques. In: Proceedings of International Conference on Pattern Recognition, Turkey, pp. 493–496 (2010).
499.
Wang, J., Zhua, S., Gonga, Y.: Resolution enhancement based on learning the sparse association of image patches. Pattern Recognit. Lett. 31, 1–10 (2010)
500.
Xiong, Z., Sun, X., Wu, F.: Robust web image/video super-resolution. IEEE Trans. Image Process. 19(9), 2017–2028 (2010)MathSciNet
501.
Yamaguchi, T., Fukuda, H., Furukawa, R., Kawasaki, H., Sturm, P.: Video deblurring and super-resolution technique for multiple moving objects. In: Proceedings of Asian Conference on Computer Vision, New Zeeland (2010).
502.
Yan, Z., Lu, Y., Yan, H.: Reducing the spiral CT slice thickness using super resolution. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 593–596 (2010).
503.
Yan, H., Sun, J., Du, L.: Face hallucination based on independent residual features. In: Proceedings of IEEE International Conference on Image and Signal Processing, China, pp. 1074–1077 (2010).
504.
Yang, M.C., Chu, C.T., Wang, Y.C.F.: Learning sparse image representation with support vector regression for single-image super-resolution. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 1973–1976 (2010).
505.
Yang, X., Su, G., Chen, J., Moon, Y.: Restoration of low resolution car plate images using PCA based image super-resolution. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2789–2792 (2010).
506.
Yang, J., Wright, J., Huang, T., Ma, Y.: Image super-resolution via sparse representation. IEEE Trans. Image Process. 19(11), 2861–2873 (2010)MathSciNet
507.
Yoshikawa, A., Suzuki, S., Goto, T., Hirano, S., Sakurai, M.: Super resolution image reconstruction using total variation regularization and learning-based method. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 1993–1996 (2010).
508.
Yuan, Q., Zhang, L., Shen, H., Li, P.: Adaptive multiple-frame image super-resolution based on U-curve. IEEE Trans. Image Process. 19(12), 3157–3170 (2010)MathSciNet
509.
Zhang, L., Zhang, H., Shen, H., Li, P.: A super-resolution reconstruction algorithm for surveillance images. Signal Process. 90(3), 848–859 (2010)MATHMathSciNet
510.
Zheng, H., Bouzerdoum, A., Phung, S.L.: Wavelet based nonlocal-means super-resolution for video sequences. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 2817–2020 (2010).
511.
Zou, W.W.W., Yuen, P.C.: Learning the relationship between high and low resolution images in kernel space for face super resolution. In: Proceedings of International Conference on Pattern Recognition, Turkey, pp. 1153–1155 (2010).
512.
Arycan, Z., Frossard, P.: Joint registration and super-resolution with omnidirectional images. IEEE Trans. Image Process. 20(11), 3151–3162 (2011)MathSciNet
513.
Babacan, S.D., Molina, R., Katsaggelos, A.K.: Variational Bayesian super resolution. IEEE Trans. Image Process. 20(4), 984–999 (2011)MathSciNet
514.
Chainais, P., Koenig, E., Delouille, V., Hochedez, J.F.: Virtual super resolution of scale invariant textured images using multifractal stochastic processes. J. Math. Imaging Vis. 39, 28–44 (2011)MATHMathSciNet
515.
Cheng, M.H., Chen, H.Y., Leou, J.J.: Video super-resolution reconstruction using a mobile search strategy and adaptive patch size. Signal Process. 91, 1284–1297 (2011)
516.
Choi, K., Kim, C., Kang, M.H., Ra, J.B.: Resolution improvement of infrared images using visible image information. IEEE Trans. Image Process. 18(10), 611–614 (2011)
517.
Demirel, H., Anbarjafari, G.: Image resolution enhancement by using discrete and stationary wavelet decomposition. IEEE Trans. Image Process. 20(5), 1458–1460 (2011)MathSciNet
518.
Dong, W., Zhang, L., Shi, G., Wu, X.: Image deblurring and super-resolution by adaptive sparse domain selection and adaptive regularization. IEEE Trans. Image Process. 20(7), 1838–1856 (2011)
519.
Gao, X., Wang, Q., Li, X., Tao, D., Zhang, K.: Zernike-moment-based image super resolution. IEEE Trans. Image Process. 20(10), 2738–2747 (2011)MathSciNet
520.
Giachetti, A., Asuni, N.: Real-time artifact-free image upscaling. IEEE Trans. Image Process. 20(10), 2760–2768 (2011)MathSciNet
521.
He, H., Siu, W.C.: Single image super-resolution using Gaussian process regression. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA, pp. 449–456 (2011).
522.
He, R., Zhang, Z.: Locally affine patch mapping and global refinement for image super-resolution. Pattern Recognit. 44, 2210–2219 (2011)
523.
Hu, Y., Lam, K.M., Qiu, G., Shen, T.: From local pixel structure to global image super-resolution: a new face hallucination framework. IEEE Trans. Image Process. 20(2), 433–445 (2010)MathSciNet
524.
Hu, Y., Lam, K.M., Shen, T., Wang, W.: A novel kernel-based framework for facial-image hallucination. Image Vis. Comput. 29, 219–229 (2011)
525.
Huang, K., Hu, R., Han, Z., Lu, T., Jiang, J., Huang, K., Wang, F.: A face super-resolution method based on illumination invariant feature. In: Proceedings of IEEE International Conference on Multimedia Technology, China (2011).
526.
Huang, H., Wu, N.: Fast facial image super-resolution via local linear transformations for resource-limited applications. IEEE Trans. Circuits Syst. Video Technol. 21(10), 1363–1377 (2011)
527.
Jung, M., Bresson, X., Chan, T.F., Vese, L.A.: Nonlocal Mumford-Shah regularizers for color image restoration. IEEE Trans. Image Process. 20(6), 1583–1598 (2011)MathSciNet
528.
Jung, C., Jiao, L., Liu, B., Gong, M.: Position-patch based face hallucination using convex optimization. IEEE Signal Process. Lett. 18(6), 367–369 (2011)
529.
Karam, L.J., Sadaka, N.G., Ferzli, R., Ivanovski, Z.A.: An efficient selective perceptual-based super-resolution estimator. IEEE Trans. Image Process. 20(12), 3470–3482 (2011)MathSciNet
530.
Keller, S.H., Lauze, F., Nielsen, M.: Video super-resolution using simultaneous motion and intensity calculations. IEEE Trans. Image Process. 20(7), 1870–1884 (2011)MathSciNet
531.
Kramer, P., Benois-Pineau, J., Domenger, J.: Local object-based super-resolution mosaicing from low-resolution video. Signal Process. 91, 1771–1780 (2011)
532.
Liu, C., Sun, D.: A bayesian approach to adaptive video super resolution. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA, pp. 209–216 (2011).
533.
Lu, J., Min, D., Pahwa, R.S., Do, M.N.: A revisit to MRF-based depth map super-resolution and enhancement. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 985–988 (2011).
534.
Milanfar, P.: Super-Resolution Imaging. CRC Press, USA, Taylor & Francis Group, London (2011)
535.
Mochizuki, Y., Kameda, Y., Imiya, A., Sakai, T., Imaizumi, T.: Variational method for super-resolution optical flow. Signal Process. 91, 1535–1567 (2011)MATH
536.
Mudenagudi, U., Banerjee, S., Kalra, P.K.: Space-time super-resolution using graph-cut optimization. IEEE Trans. Pattern Anal. Mach. Intell. 33(5), 995–1008 (2011)
537.
Nasrollahi, K.: From face detection to face super-resolution using face quality assessment. PhD thesis, Aalborg University, Denmark (2011).
538.
Nasrollahi, K., Moeslund, T.B.: Extracting a good quality frontal face image from a low-resolution video sequence. IEEE Trans. Circuits Syst. Video Technol. 21(10), 1353–1362 (2011)
539.
Omer, O.A., Tanaka, T.: Region-based weighted-norm with adaptive regularization for resolution enhancement. Digit. Signal Process. Lett. 21, 508–516 (2011)
540.
Patel, V., Modi, C.K., Paunwala, C.N., Patnaik, S.: Hybrid approach for single image super resolution using ISEF and IBP. In: Proceedings of International Conference on Communication Systems and Network Technologies, India (2011).
541.
Petrou, M., Jaward, M.H., Chen, S., Briers, M.: Super-resolution in practice: the complete pipeline from image capture to super-resolved subimage creation using a novel frame selection method. Mach. Vis. Appl. 23(3), 441–459 (2012)
542.
Purkait, P., Chanda, B.: Morphologic gain-controlled regularization for edge-preserving super-resolution image reconstruction. Signal Image Video Process. 7(5), 925–938 (2013)
543.
Shahar, O., Faktor, A., Irani, M.: Space-time super-resolution from a single video. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA, pp. 3353–3360 (2011).
544.
Shen, M., Xue, P., Wang, C.: Down-sampling based video coding using super-resolution technique. IEEE Trans. Circuits Syst. Video Technol. 21(6), 755–765 (2011)
545.
Song, B.C., Jeong, S.C., Choi, Y.: Video super-resolution algorithm using bi-directional overlapped block motion compensation and on-the-fly dictionary training. IEEE Trans. Circuits Syst. Video Technol. 21(3), 274–285 (2011)
546.
Sun, J., Sun, J., Xu, Z., Shum, H.Y.: Gradient profile prior and its applications in image super-resolution and enhancement. IEEE Trans. Circuits Syst. Video Technol. 20(6), 1529–1542 (2011)
547.
Szydzik, T., Callico, G.M., Nunez, A.: Efficient FPGA implementation of a high-quality super-resolution algorithm with real-time performance. IEEE Trans. Consum. Electron. 57(2), 664–672 (2011)
548.
Tian, Y., Yap, K.H., He, Y.: Vehicle license plate super-resolution using soft learning prior. Multimed, Tools Appl 60(3), 519–535 (2012)
549.
Wu, W., Liu, Z., He, X.: Learning-based super resolution using kernel partial least squares. Signal Process. Image Commun. 29, 394–406 (2011)
550.
Yang, Y., Wang, Z.: A new image super-resolution method in the wavelet domain. In: Proceedings of IEEE International Conference on Image and Graphics, China, pp. 163–167 (2011).
551.
Zhang, W., Cham, W.K.: Hallucinating face in the DCT domain. IEEE Trans. Image Process. 20(10), 2769–2779 (2011)MathSciNet
552.
Zibetti, M.V.W., Bazan, F.S.V., Mayer, J.: Estimation of the parameters in regularized simultaneous super-resolution. Pattern Recognit. Lett. 32, 69–78 (2011)
553.
Bengtsson, T., Gu, I. Y-H., Viberg, M., Lindstrom, K.: Regularized optimization for joint super-resolution and high dynamic range image reconstruction in a perceptually uniform domain. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan, pp. 1097–1100 (2012).
554.
Bevilacqua, M., Roumy, A., Guillemot, C., Morel, M-L. A.: Neighbor embedding based single-image super-resolution using semi-nonnegative matrix factorization. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan, pp. 1289–1292 (2012).
555.
Bouzari, H.: An improved regularization method for artifact rejection in image super-resolution. Signal Image Video Process. 6, 125–140 (2012)
556.
Chen, J., Yanez, J.N., Achim, A.: Video super-resolution using generalized Gaussian Markov random fields. IEEE Signal Process. Lett. 19(2), 63–69 (2012)
557.
Fookes, C., Lin, F., Chandran, V., Sridharan, S.: Evaluation of image resolution and super-resolution on face recognition performance. J. Vis. Commun. Image Represent. 23, 75–93 (2012)
558.
Gao, X., Zhang, K., Tao, D., Li, X.: Image super-resolution with sparse neighbor embedding. IEEE Trans. Image Process. 21(7), 3194–3205 (2012)MathSciNet
559.
Gao, X., Zhang, K., Tao, D., Li, X.: Joint learning for single image super-resolution via a coupled constraint. IEEE Trans. Image Process. 21(2), 469–480 (2012)MathSciNet
560.
Ho, T.C., Zeng, B.: Image super-resolution by curve fitting in the threshold decomposition domain. J. Vis. Commun. Image Represent. 23, 208–221 (2012)
561.
Huhle, B., Schairer, T., Jenke, P., Straber, W.: Fusion of range and color images for denoising and resolution enhancement with a non-local filter. Comput. Vis. Image Underst. 114, 1336–1345 (2012)
562.
Hui, Z., Lam, J.-M.: An efficient local-structure-based face-hallucination method. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan, pp. 1265–1268 (2012).
563.
Hung, E.M., de Queiroz, R.L., Brandi, F., de Oliveira, K.F., Mukherjee, D.: Video super-resolution using codebooks derived from key-frames. IEEE Trans. Circuits Syst. Video Technol. 22(9), 1321–1331 (2012)
564.
Hung, K.-W., Siu, W.-C.: Single image super-resolution using iterative Wiener filter. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan, pp. 1269–1272 (2012).
565.
Islam, R., Lambert, A.J., Pickering, M.R.: Super resolution of 3d MRI images using a Gaussian scale mixture model constraint. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan, pp. 849–852 (2012).
566.
Islam, R., Lambert, A.J., Pickering, M.R.: Super resolution of 3d MRI images using a bivariate Laplacian mixture model constraint. In: Proceedings of IEEE International Symposium on Biomedical Imaging, Spain, pp 1499–1502 (2012).
567.
Islam, M.M., Islam, M.N., Asari, V.K., Karim, M.A.: Single image super-resolution in frequency domain. In: Proceedings of IEEE Southwest Symposium on Image Analysis and Interpretation, USA, pp. 53–56 (2012).
568.
Ito, I., Kiya, H.: A new technique of non-iterative super-resolution without boundary distortion. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan, pp. 1273–1275 (2012).
569.
Jiang, J., Hu, R., Han, Z., Huang, J., Lu, T.: Efficient single image super-resolution via graph embedding. In: Proceedings of IEEE International Conference on Multimedia and Expo, Australia (2012).
570.
Jiang, J., Hu, R., Han, Z., Lu, T., Huang, J.: A super-resolution method for low-quality face image through RBF-PLS regression and neighbor embedding. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan (2012).
571.
Jiang, J., Hu, R., Han, Z., Lu, T., Huang, J.: Surveillance face hallucination via variable selection and manifold learning. In: Proceedings of IEEE International Symposium on Circuits and Systems, Korea, pp. 2681–2683 (2012).
572.
Jiang, J., Hu, R., Han, Z., Lu, T., Huang, J.: Position-patch based face hallucination via locality-constrained representation. In: Proceedings of IEEE International Conference on Multimedia and Expo, Australia (2012).
573.
Jing, G., Shi, Y., Kong, D., Ding, W., Yin, B.: Image super-resolution based on multi-space sparse representation. Multimed. Tools Appl. 70(2), 741–755 (2014)
574.
Kim, D., Yoon, K.: High quality depth map up-sampling robust to edge noise of range sensors. In: Proceedings of IEEE International Conference on Image Processing, pp. 553–556 (2012).
575.
Katsuki, T., Inoue, M.: Posterior mean super-resolution with a compound Gaussian Markov random field prior. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan, pp. 841–844 (2012).
576.
Katsuki, T., Inoue, M.: Posterior mean super-resolution with a causal Gaussian Markov random field prior. IEEE Trans. Image Process. 21(7), 3182–3193 (2012)MathSciNet
577.
Kulkarni, N., Nagesh, P., Gowda, R., Li, B.: Understanding compressive sensing and sparse representation-based super-resolution. IEEE Trans. Circuits Syst. Video Technol. 22(5), 778–789 (2012)
578.
Li, D., Simske, S.: Fast single image super-resolution by self-trained filtering. In: Perception and Machine Intelligence. Lecture Notes in Computer Science, Advanced Intelligent Computing Theories and Applications with Aspects of Artificial Intelligence, vol. 6839, pp. 469–475 (2012).
579.
Li, Y., Xue, T., Sun, L., Liu, J.: Joint example-based depth map super-resolution. In: Proceedings of IEEE International Conference on Multimedia and Expo, Australia (2012).
580.
Lu, X., Yuan, H., Yan, P., Yuan, Y., Li, X.: Geometry constrained sparse coding for single image super-resolution. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA, pp. 1648–1655 (2012).
581.
Ma, L., Zhao, D., Gao, W.: Learning-based image restoration for compressed images. Signal Process. Image Commun. 27(1), 54–65 (2012)
582.
Morin, R., Basarab, A., Kouame, D.: Alternating direction method of multipliers framework for super-resolution in ultrasound imaging. In: Proceedings of IEEE International Symposium on Biomedical Imaging, Spain (2012).
583.
Nasir, H., Stankovic, V., Marshall, S.: Singular value decomposition based fusion for super-resolution image reconstruction. Signal Process. Image Commun. 27, 180–191 (2012)
584.
Naleer, H.M.M., Lu, Y.: A new two-step face hallucination through block of coefficients. In: Proceedings of IEEE International Conference on Computer Science and Automation Engineering, China (2012).
585.
Nema, M.K., Rakshit, S., Chaudhuri, S.: Fast computation of edge model representation for image sequence super-resolution. Lecture Notes in Computer Science, Perception and Machine Intelligence 7143, 252–259 (2012)
586.
Nguyen, K., Sridharan, S., Denman, S., Fookes, C.: Feature-domain super-resolution framework for Gabor-based face and iris recognition. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA, pp. 2642–2649 (2012).
587.
Ogawa, Y., Ariki, Y., Takiguchi, T.: Super-resolution by GMM based conversion using self-reduction image. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan, pp. 1285–1288 (2012).
588.
Panagiotopoulou, A., Anastassopoulos, V.: Super-resolution image reconstruction techniques: trade-offs between the data-fidelity and regularization terms. Inf. Fusion 13, 185–195 (2012)
589.
Pelletier, S., Cooperstock, J.R.: Preconditioning for edge-preserving image super resolution. IEEE Trans. Image Process. 21(1), 67–79 (2012)MathSciNet
590.
Peng, Y., Yang, F., Dai, Q., Xu, W., Vetterli, M.: Super-resolution from unregistered aliased images with unknown scalings and shifts. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan, pp. 857–860 (2012).
591.
Purkait, P., Chanda, B.: Super resolution image reconstruction through Bregman iteration using morphologic regularization. IEEE Trans. Image Process. 21(9), 4029–4039 (2012)MathSciNet
592.
Singh, M., Lu, C., Basu, A., Mandal, M.: Choice of low resolution sample sets for efficient super-resolution signal reconstruction. J. Vis. Commun. Image Represent. 23, 194–207 (2012)
593.
Su, H., Wu, Y., Zhou, J.: Super-resolution without dense flow. IEEE Trans. Image Process. 21(4), 1782–1795 (2012)MathSciNet
594.
Su, H., Tang, L., Wu, Y., Tretter, D., Zhou, J.: Spatially adaptive block-based super-resolution. IEEE Trans. Image Process. 21(3), 1031–1045 (2012)MathSciNet
595.
Sun, L., Hays, H.: Super-resolution from Internet-scale scene matching. In: Proceedings of IEEE International Conference on Computational Photography, USA, pp. 1–12 (2012).
596.
Tang, Y., Yuan, Y., Yan, P., Li, X.: Greedy regression in sparse coding space for single-image super-resolution. J. Vis Commun. Image Represent. (2012) (in press).
597.
Tian, Y., Yap, K.-H.: Multi-frame super-resolution from observations with zooming motion. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan, pp. 1257–1260 (2012).
598.
Wang, J., Zhu, S.: Resolution-invariant coding for continuous image super-resolution. Neurocomputing 82, 21–28 (2012)
599.
Wu, B., Li, C., Zhan, X.: Integrating spatial structure in super-resolution mapping of hyper-spectral image. Procedia Eng. 29, 1957–1962 (2012)
600.
Yan, H., Sun, J., Zhang, C.: Low-resolution face recognition with variable illumination based on differential images. In: Proceedings on International Conference on Intelligent Information Hiding and Multimedia, Signal Processing, pp. 146–149 (2012).
601.
Yang, M.-C., Huang, D.-A., Tsai, C.-Y., Wang, Y.-C. F.: Self-learning of edge-preserving single image super-resolution via contourlet transform. In: IEEE International Conference on Multimedia and Expo, Australia (2012).
602.
Yang, S., Wang, M., Chen, Y., Sun, Y.: Single-image super-resolution reconstruction via learned geometric dictionaries and clustered sparse coding. IEEE Trans. Image Process. 21(9), 4016–4028 (2012)MathSciNet
603.
Yang, J., Wang, Z., Lin, Z., Cohen, S., Huang, T.: Coupled dictionary training for image super-resolution. IEEE Trans. Image Process. 21(8), 3467–3478 (2012)MathSciNet
604.
Yldrm, D., Gungor, O.: A novel image fusion method using IKONOS satellite images. J. Geod. Geoinf. 1(1), 27–34 (2012)
605.
Yin, H., Li, S., Fang, L.: Simultaneous image fusion and super-resolution using sparse representation. Inf. Fusion (2012) (in press).
606.
Yoshida, T., Takahashi, T., Deguchi, D., Ide, I., Murase, H.: Robust face super-resolution using free-form deformations for low-quality surveillance video. In: Proceedings of IEEE International Conference on Multimedia and Expo, Australia (2012).
607.
Yuan, Q., Zhang, L., Shen, H.: Multiframe super-resolution employing a spatially weighted total variation model. IEEE Trans. Circuits Syst. Video Technol. 22(3), 379–392 (2012)
608.
Zeng, X., Huang, H.: Super-resolution method for multiview face recognition from a single image per person using nonlinear mappings on coherent features. IEEE Signal Process. Lett. 19(4), 195–198 (2012)MathSciNet
609.
Zhang, K., Gao, X., Tao, D., Li, X.: Multi-scale dictionary for single image super-resolution. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA, pp. 1114–1121 (2012).
610.
Zhang, D., He, J., Du, M.: Morphable model space based face super-resolution reconstruction and recognition. Image Vis. Comput. 30(2), 100–108 (2012)
611.
Zhang, X., Jiang, J., Peng, S.: Commutability of blur and affine warping in super-resolution with application to joint estimation of triple-coupled variables. IEEE Trans. Image Process. 21(4), 1796–1808 (2012)MathSciNet
612.
Zhang, X., Tang, M., Tong, R.: Robust super resolution of compressed video. Vis. Comput. 28(12), 1167–1180 (2012)
613.
Zhang, H., Zhang, Y., Li, H., Huang, T.S.: Generative Bayesian image super resolution with natural image prior. IEEE Trans. Image Process. 21(9), 4054–4067 (2012)MathSciNet
614.
Zhang, H., Zhang, L., Shen, H.: A super-resolution reconstruction algorithm for hyper spectral images. Signal Process. 92(9), 2082–2096 (2012)MathSciNet
615.
Zhang, Y., Wu, G., Yap, P.-T., Feng, Q., Lian, J., Chen, W., Shen, D.: Reconstruction of super-resolution lung 4d-CT using patch-based sparse representation. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, USA, pp. 925–931 (2012).
616.
Zhou, F.: A coarse-to-fine subpixel registration method to recover local perspective deformation in the application of image super-resolution. IEEE Trans. Image Process. 21(1), 53–66 (2012)MathSciNet
617.
Zhu, S., Zeng, B., Yan, S.: Image super-resolution via low-pass filter based multi-scale image decomposition. In: Proceedings of IEEE International Conference on Multimedia and Expo, Australia (2012).
618.
Zhuo, Y., Liu, J., Ren, J., Guo, Z.: Nonlocal based super resolution with rotation invariance and search window relocation. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Japan, pp. 853–857 (2012).
619.
Zou, W.W.W., Yuen, P.C.: Very low resolution face recognition problem. IEEE Trans. Image Process. 21(1), 327–340 (2012)MathSciNet
Metadaten
Titel
Super-resolution: a comprehensive survey
verfasst von
Kamal Nasrollahi
Thomas B. Moeslund
Publikationsdatum
01.08.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 6/2014
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-014-0623-4

Weitere Artikel der Ausgabe 6/2014

Machine Vision and Applications 6/2014 Zur Ausgabe

Original Paper

Fast automatic medical image segmentation based on spatial kernel fuzzy c-means on level set method

Original Paper

Automatic plant identification from photographs

Original Paper

A traverse inspection system for high precision visual on-loom fabric defect detection

Original Paper

Multilayer background modeling under occlusions

Original Paper

Automatic optical phase identification of micro-drill bits based on improved ASM and bag of shape segment in PCB production

Original Paper

Background subtraction by combining Temporal and Spatio-Temporal histograms in the presence of camera movement