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Blind source separation of images based on general cross correlation of linear operators

[+] Author Affiliations
Noam Shamir

Ben-Gurion University, Department of Electro-Optics Engineering, P.O. 653, Beer Sheva 84105, Israel

Zeev Zalevsky

Bar-Ilan University, School of Engineering, Ramat-Gan 52900, Israel

Leonid Yaroslavsky

Tel-Aviv University, School of Electrical Engineering, Tel-Aviv 69978, Israel

Bahram Javidi

University of Connecticut, Electrical & Computer Engineering Department, Storrs, Connecticut 06269

J. Electron. Imaging. 20(2), 023017 (June 30, 2011). doi:10.1117/1.3596620
History: Received June 04, 2010; Revised April 03, 2011; Accepted May 09, 2011; Published June 30, 2011; Online June 30, 2011
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Blind source separation is a process in which mixed signals, obtained as a linear combination of various source signals, are decomposed into their original sources. The source signals and their mixture weights are unknown, but a priori information about their statistical behavior and mixing model is available. In this paper, a new algorithm based on generalized cross correlation linear-operator set is proposed. This algorithm significantly improves source-separation quality compared to several other well-known algorithms, such as subband decomposition independent component analysis, block Gaussian likelihood, and convex analysis of mixtures of non-negative sources.

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© 2011 SPIE and IS&T

Citation

Noam Shamir ; Zeev Zalevsky ; Leonid Yaroslavsky and Bahram Javidi
"Blind source separation of images based on general cross correlation of linear operators", J. Electron. Imaging. 20(2), 023017 (June 30, 2011). ; http://dx.doi.org/10.1117/1.3596620


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