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Journal of Electronic Imaging

Blind source separation of images based upon fractional autocorrelation
Author(s): Noam Shamir; Natan S. Kopeika; Zeev Zalevsky
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Paper Abstract

Blind source separation (BSS) is a process in which mixed signals are separated into their original sources. Both the sources as well as the mixing coefficients are unknown but a priori information about statistical behavior and about the mixing model might be available. We here suggest a generalization of our previous research that showed a new BSS algorithm based on general cross correlation linear operators applied on the sources that are to be separated. In that approach in cases of negligible cross-correlation between the source signals, a very good separation could be obtained. Here we propose to use the fractional Fourier transform in order to reduce the correlation between the source signals and to further enhance the obtained separation performance. We present reduced dependence on the cross-correlation between the source images, resulting in better separation of the mixed sources.

Paper Details

Date Published: 3 January 2013
PDF: 9 pages
J. Electron. Imag. 21(4) 043027 doi: 10.1117/1.JEI.21.4.043027
Published in: Journal of Electronic Imaging Volume 21, Issue 4
Show Author Affiliations
Noam Shamir, Ben-Gurion Univ. of the Negev (Israel)
Natan S. Kopeika, Ben-Gurion Univ. of the Negev (Israel)
Zeev Zalevsky, Bar-Ilan Univ. (Israel)

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