1 April 2011 Blind source separation of images based on general cross correlation of linear operators
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Abstract
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.
© (2011) Society of Photo-Optical Instrumentation Engineers (SPIE)
Noam Shamir, Noam Shamir, Zeev Zalevsky, Zeev Zalevsky, Leonid P. Yaroslavsky, Leonid P. Yaroslavsky, Bahram Javidi, Bahram Javidi, } "Blind source separation of images based on general cross correlation of linear operators," Journal of Electronic Imaging 20(2), 023017 (1 April 2011). https://doi.org/10.1117/1.3596620 . Submission:
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