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Journal of Scientific Computing

Erschienen in:

01.07.2014

Kullback–Leibler Divergence Based Composite Prior Modeling for Bayesian Super-Resolution

verfasst von: Wen-Ze Shao, Hai-Song Deng, Zhi-Hui Wei

Erschienen in: Journal of Scientific Computing | Ausgabe 1/2014

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Abstract

This paper proposes to adaptively combine the known total variation model and more recent Frobenius norm regularization for multi-frame image super-resolution (SR). In contrast to existing literature, in this paper both the composite prior modeling and posterior variational optimization are achieved in the Bayesian framework by utilizing the Kullback–Leibler divergence, and hyper-parameters related to the composite prior and noise statistics are all determined automatically, resulting in a spatially adaptive SR reconstruction method. Experimental results demonstrate that the new approach can generate a super-resolved image with higher signal-to-noise ratio and better visual perception, not only image details better preserved but also staircase effects better suppressed.

Vorheriger Artikel Lossy Compression in Optimal Control of Cardiac Defibrillation

Nächster Artikel Domain Decomposition Methods for Nonlocal Total Variation Image Restoration

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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), 1–16 (2007)

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, pp. 2–11 (2004)

Li, F., Jia, X., Fraser, D., Andrew, L.: Super resolution for remote sensing images based on a universal hidden Markov tree model. IEEE Trans. Geosci. Remote Sens. 48(3), 1270–1278 (2010)CrossRef

Yang, J., Wright, J., Huang, T., Ma, Y.: Image superresolution via sparse representation. IEEE Trans. Image Process. 19(11), 2861–2873 (2010)CrossRefMathSciNet

Robinson, M.D., Chiu, S.J., Lo, J.Y., Toth, C.A., Izatt, J.A., Farsiu, S.: Novel applications of super-resolution in medical imaging. In: Milanfar, Peyman (ed.) Super-Resolution Imaging, pp. 383–412. CRC Press, Boca Raton (2010)

Kang, M., Chaudhuri, S. (ed.): Super-resolution image reconstruction. IEEE Signal Process. Mag. 20(3), 19–20 (2003)

Milanfar, P.: Super-Resolution Imaging. CRC Press, New York (2011)

Katsaggelos, A.K., Molina, R., Mateos, J.: Super Resolution of Images and Video. Morgan and Claypool, San Rafael (2007)

Hardie, R.C., Barnard, K.J., Armstrong, E.E.: Join MAP registration and high resolution image estimation using a sequence of undersampled images. IEEE Trans. Image Process. 6(12), 1621–1633 (1997)CrossRef

10.

He, H., Kondi, L.P.: MAP based resolution enhancement of video sequences using a Huber-Markov random field image prior model. Int. Conf. Image Process. 3, 933–936 (2003)

11.

Marquina, A., Osher, S.J.: Image super-resolution by TV-regularization and Bregman iteration. J. Sci. Comput. 37(3), 367–382 (2008)CrossRefMATHMathSciNet

12.

Farsiu, S., Robinson, M.D., Elad, M., Milanfar, P.: Fast and robust multiframe super resolution. IEEE Trans. Image Process. 13(10), 1327–1344 (2004)CrossRef

13.

Zeng, W.L., Lu, X.B.: A robust variational approach to super-resolution with nonlocal TV regularisation term. The Imaging Science Journal (2012) accepted

14.

Babacan, S.D., Molina, R., Katsaggelos, A.K.: Variational Bayesian super resolution. IEEE Trans. Image Process. 20(4), 984–999 (2011)CrossRefMathSciNet

15.

Lefkimmiatis, S., Bourquard, A., Unser, M.: Hessian-based norm regularization for image restoration with biomedical applications. IEEE Trans. Image Process. 21(3), 983–995 (2012)CrossRefMathSciNet

16.

Lysaker, M., Tai, X.-C.: Iterative image restoration combining total variation minimization and a second-order functional. Int. J. Comput. Vision. 66(1), 5–18 (2006)CrossRefMATH

17.

Yang, J., Zhang, Y., Yin, W.: A fast alternating direction method for TVL1-L2 signal reconstruction from partial fourier data. IEEE J. Sel. Top. Signal Process. 4(2), 288–297 (2010)CrossRef

18.

Shao, W.-Z., Deng, H.-S., Wei, Z.-H.: Multi-Parseval frame-based nonconvex sparse image deconvolution. Opt. Eng. 51(6), 067008–067008-12 (2012)CrossRef

19.

Li, F., Shen, C., Fan, J., Shen, C.: Image restoration combining a total variational filter and a fourth-order filter. J. Visual Commun. Image Represent 18(4), 322–330 (2007)CrossRef

20.

Mignotte, M.: Fusion of regularization terms for image restoration. J. Electron. Imaging 19, 033004 (2010)CrossRefMathSciNet

21.

Afonso, M.V., Bioucas-Dias, J.M., Figueiredo, M.A.T.: Fast image recovery using variable splitting and constrained optimization. IEEE Trans. Image Process. 19(9), 2345–2356 (2010)CrossRefMathSciNet

22.

Villena, S., Vega, M., Babacan, S.D., Molina, R., Katsaggelos, A.K.: Using the Kullback-Leibler divergence to combine image priors in super-resolution image reconstruction. IEEE 17th international conference on image processing, pp. 893–896 (2010)

23.

Oliveira, J., Figueiredo, M., Bioucas-Dias, J.: Adaptative total variation image deblurring: a majorization-minimization approach. Signal Process. 89(9), 1683–1693 (2009)CrossRefMATH

24.

Tipping, M.E., Bishop, C.M.: Bayesian Image Super-Resolution. Advances in Neural Information Processing Systems (15). MIT Press, Cambridge (2003)

25.

Kanemura, A., Maeda, S.-I., Ishii, S.: Superresolution with compound Markov random fields via the variational EM algorithm. Neural Netw. 22(7), 1025–1034 (2009)CrossRef

26.

Pickup, L.C., Capel, D.P., Roberts, S.J., Zisserman, A.: Bayesian methods for image super-resolution. Comput. J. 52(1), 101–113 (2009)CrossRef

27.

Zomet, A., Rav-Acha, A., Peleg, S.: Robust super-resolution. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 645–650 (2001)

28.

Shao, W. Z., Deng, H. S., Wei, Z. H.: A posterior mean approach for MRF-based spatially adaptive multi-frame image super-resolution. Signal Image Video Process. (2013). doi:10.1007/s11760-013-0458-x

Titel: Kullback–Leibler Divergence Based Composite Prior Modeling for Bayesian Super-Resolution
verfasst von: Wen-Ze Shao
Hai-Song Deng
Zhi-Hui Wei
Publikationsdatum: 01.07.2014
Verlag: Springer US
Erschienen in: Journal of Scientific Computing / Ausgabe 1/2014
Print ISSN: 0885-7474
Elektronische ISSN: 1573-7691
DOI: https://doi.org/10.1007/s10915-013-9784-y

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