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
Erschienen in:
An Image Steganalysis Algorithm Based on Rotation Forest Transformation and Multiple Classifiers Ensemble Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Multi-focus Image Fusion Method Based on NSST and IICM

verfasst von : Yang Lei

Erschienen in: Advances in Internetworking, Data & Web Technologies

Verlag: Springer International Publishing

Einloggen

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

search-config
loading …

Abstract

Multi-focus image fusion is a classic issue in the field of image processing. How to extract and fuse the in-focus information from the source images into the single one is the key to resolving the above problem. As a novel multi-resolution analysis tool, non-subsampled shearlet transform (NSST) not only has better information capturing ability, but also owns a comparatively lower computational complexity compared with non-subsampled contourlet transform (NSCT). Intersecting cortical model (ICM) is the third generation of artificial neural network, and it can be viewed as the improved version of pulse-coupled neural network. The superiority of ICM lies in that it has much fewer parameters and better function mechanism. In this paper, a novel method for multi-focus image fusion based on NSST and improved ICM is presented. On the one hand, NSST is responsible for decomposing source images and reconstructing sub-images. On the other hand, ICM is used to complete the coefficients selecting of sub-images. Experimental results demonstrate that the proposed method has better performance compared with the current typical ones.

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 "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

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
Vorheriges Kapitel Cyber-Attack Risks Analysis Based on Attack-Defense Trees
Nächstes Kapitel Pilot Contamination Elimination in Massive MIMO Systems
Literatur
1.
Yang, Y., Que, Y., Huang, S., Lin, P.: Multimodal sensor medical image fusion based on type-2 fuzzy logic in NSCT domain. IEEE Sens. J. 16, 3735–3745 (2016)CrossRef
2.
Ghahremani, M., Ghassemian, H.: Remote sensing image fusion using ripplet transform and compressed sensing. IEEE Geosci. Remote Sens. Lett. 12, 502–506 (2015)CrossRef
3.
Burt, P.J., Kolcznski, R.J.: Enhanced image capture through fusion. Proc. Conf. Comput. Vis. 1, 173–182 (1993)
4.
Palsson, F., Sveinsson, J.R., Ulfarsson, M.O., Benediktsson, J.A.: Model-based fusion of multi- and hyperspectral images using PCA and wavelets. IEEE Trans. Geosci Remot. Sen. 53, 2652–2663 (2015)CrossRef
5.
Mitianoudis, N., Stathaki, T.: Optimal contrast correction for ICA-based fusion of multimodal images. IEEE Sens. J. 8, 2016–2026 (2008)CrossRef
6.
Broussard, R.P., Rogers, S.K., Oxley, M.E., Tarr, G.L.: Physiologically motivated image fusion for object detection using a pulse coupled neural network. IEEE Trans. Neur. Net. 10, 554–563 (1999)CrossRef
7.
Kinser, J.M.: Simplified pulse-coupled neural network. Proc. Conf. Appl. Arti. Neur. Net. 1, 563–567 (1996)
8.
Ali, F.E., El-Dokany, I.M., Saad, A.A., El-Samie, F.E.A.: Curvelet fusion of MR and CT images. Progr. Electromagn. Res. C 3, 215–224 (2008)CrossRefMATH
9.
Pertuz, S., Puig, D., Garcia, M.A., Fusiello, A.: Genaration of all-in-focus images by noise-robust selective fusion of limited depth-of-field images. IEEE Trans. Image Process. 22, 1242–1251 (2013)MathSciNetCrossRef
10.
Do, M.N., Vetterli, M.: The finite ridgelet transform for image representation. IEEE Trans. Image Process. 12, 16–28 (2003)MathSciNetCrossRefMATH
11.
Candes, E.J., Donoho, D.L.: Curvelets: a surprisingly effective non-adaptive representation for objects with edges. Stanford University, CA (1999)
12.
Cao, L., Jin, L., Tao, H., Li, G., Zhang, Z., Zhang, Y.: Multi-focus image fusion based on spatial frequency in discrete cosine transform domain. IEEE Signal Process. Lett. 22, 220–224 (2015)CrossRef
13.
Do, M.N., Vetterli, M.: The contourlet transform: an efficient directional multi-resolution image representation. IEEE Trans. Image Process. 14, 2091–2106 (2005)CrossRef
14.
Miao, Q.G., Shi, C., Xu, P.F., Yang, M., Shi, Y.B.: A novel algorithm of image fusion using shearlets. Opt. Commun. 284, 1540–1547 (2011)CrossRef
15.
Bhatnagar, G., Wu, Q.M.J., Liu, Z.: Directive contrast based multimodal medical image fusion in NSCT domain. IEEE Trans. Multimedia 15, 1014–1024 (2013)CrossRef
16.
Easley, G., Labate, D., Lim, W.Q.: Sparse directional image representation using the discrete shearlet transforms. Appl. Comput. Harmon. Anal. 25, 25–46 (2008)MathSciNetCrossRefMATH
17.
Abdullah, A., Omar, A.J., Inad, A.A.: Image mosaicing using binary edge detection algorithm in a cloud-computing environment. Int. J. Inf. Technol. Web. Eng. 11, 1–14 (2016)
18.
Sathiyamoorthi, V.: A novel cache replacement policy for web proxy caching system using web usage mining. Int. J. Inf. Technol. Web. Eng. 11, 1–13 (2016)CrossRef
19.
Sylvaine, C., Insaf, K.: Reputation, image, and social media as determinants of e-Reputation: the case of digital natives and luxury brands. Int. J. Technol. Human Interact. 12, 48–64 (2016)
20.
Wu, Z.M., Lin, T., Tang, N.J.: Explore the use of handwriting information and machine learning techniques in evaluating mental workload. Int. J. Technol. Human Interact. 12, 18–32 (2016)CrossRef
21.
Kong, W.W., Lei, Y., Ren, M.M.: Fusion method for infrared and visible images based on improved quantum theory model. Neurocomputing 212, 12–21 (2016)CrossRef
22.
Kong, W.W., Wang, B.H., Lei, Y.: Technique for infrared and visible image fusion based on non-subsampled shearlet transform and spiking cortical model. Infrared Phys. Technol. 71, 87–98 (2015)CrossRef
23.
Kong, W.W., Lei, Y., Zhao, H.X.: Adaptive fusion method of visible light and infrared images based on non-subsampled shearlet transform and fast non-negative matrix factorization. Infrared Phys. Technol. 67, 161–172 (2014)CrossRef
24.
Kong, W.W., Liu, J.P.: Technique for image fusion based on NSST domain improved fast non-classical RF. Infrared Phys. Technol. 61, 27–36 (2013)CrossRef
25.
Kong, W.W., Lei, Y.J., Lei, Y., Zhang, J.: Technique for image fusion based on non-subsampled contourlet transform domain improved NMF. Sci. China Ser. F-Inf. Sci. 53, 2429–2440 (2010)MathSciNetCrossRefMATH
26.
Kong, W.W., Lei, Y., Ma, J.: Virtual machine resource scheduling algorithm for cloud computing based on auction mechanism. Optik 127, 5099–5104 (2016)CrossRef
27.
Kong, W.W., Lei, Y., Zhao, R.: Fusion technique for multi-focus images based on NSCT-ISCM. Optik 126, 3185–3192 (2015)CrossRef
28.
Kong, W.W.: Technique for image fusion based on NSST domain INMF. Optik 125, 2716–2722 (2014)CrossRef
29.
Kong, W.W., Lei, Y.: Technique for image fusion between gray-scale visual light and infrared images based on NSST and improved RF. Optik 124, 6423–6431 (2013)CrossRef
30.
Kong, W.W., Lei, Y.: Multi-focus image fusion using biochemical ion exchange model. Appl. Soft Comput. 51, 314–327 (2017)CrossRef
31.
Cao, Y., Li, S.T., Hu, J.W.: Multi-focus image fusion by nonsubsampled shearlet transform. In: Proceedings of IEEE 6th International Conference on Image and Graphics, vol. 1, pp. 17–21 (2011)
32.
Miao, Q.G., Wang, B.S.: A novel image fusion algorithm based on local contrast and adaptive PCNN. Chin. J. Comput. 31, 875–880 (2008)CrossRef
33.
Wang, Z.B., Ma, Y.D., Gu, J.S.: Multi-focus image fusion using PCNN. Pattern Recogn. 43, 2003–2016 (2010)CrossRefMATH
34.
Yang, S.Y., Wang, M., Lu, Y.X.: Fusion of multiparametric SAR images based on SW-nonsubsampled contourlet and PCNN. Sig. Process. 89, 2596–2608 (2009)CrossRefMATH
35.
Chiorean, L., Vaida, M.F.: Medical image fusion based on discrete wavelet transform using Java technology. In: Proceedings of the ITI 2009 31st International Conference on Information Technology Interfaces, vol. 1, pp. 55–60 (2009)
36.
Cai, W., Li, M., Li, X.Y.: Infrared and visible image fusion scheme based on contourlet transform. In: Proceedings of the ICIG 2009 5th International Conference on Image and Graphics, vol. 1, pp. 516–520 (2009)
Metadaten
Titel
Multi-focus Image Fusion Method Based on NSST and IICM
verfasst von
Yang Lei
Copyright-Jahr
2018
Buch
Advances in Internetworking, Data & Web Technologies

Print ISBN: 978-3-319-59462-0

Electronic ISBN: 978-3-319-59463-7

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-59463-7_68