Regular Articles

Blind source separation of images based upon fractional autocorrelation

[+] Author Affiliations
Noam Shamir, Natan Kopeika

Ben-Gurion University, Department of Electro-Optics Engineering, Beer-Sheva 84105, Israel

Zeev Zalevsky

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

J. Electron. Imaging. 21(4), 043027 (Jan 03, 2013). doi:10.1117/1.JEI.21.4.043027
History: Received February 2, 2012; Revised November 10, 2012; Accepted November 16, 2012
Text Size: A A A

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.

Figures in this Article
© 2013 SPIE and IS&T

Citation

Noam Shamir ; Natan Kopeika and Zeev Zalevsky
"Blind source separation of images based upon fractional autocorrelation", J. Electron. Imaging. 21(4), 043027 (Jan 03, 2013). ; http://dx.doi.org/10.1117/1.JEI.21.4.043027


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.