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Journal of Electronic Imaging

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

Paper Details

Date Published: 1 April 2011
PDF: 13 pages
J. Electron. Imag. 20(2) 023017 doi: 10.1117/1.3596620
Published in: Journal of Electronic Imaging Volume 20, Issue 2
Show Author Affiliations
Noam Shamir, Ben-Gurion Univ. of the Negev (Israel)
Zeev Zalevsky, Bar-Ilan Univ. (Israel)
Leonid P. Yaroslavsky, Tel Aviv Univ. (Israel)
Bahram Javidi, Univ. of Connecticut (United States)

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