DocumentCode
2703751
Title
Blind Non-independent Image Separation Based on Independent Component Analysis
Author
Guo, Wu ; Zhang, Peng ; Wang, Runsheng
Author_Institution
NUDT, Changsha
fYear
2007
fDate
15-19 Dec. 2007
Firstpage
271
Lastpage
274
Abstract
Blind separation of mixture images which mutually independent has been solved efficiently by some independent component analysis(ICA) methods. But these methods often failed in case of the source images are statistically non-independent. A novel fixed-point FastICA algorithm based on complexity pursuit is presented in this paper and with the algorithm the mixed images which not mutually independent can be separated successfully. Experimental results demonstrate the efficiency of our proposed method.
Keywords
blind source separation; computational complexity; image processing; independent component analysis; blind nonindependent image separation; complexity pursuit; fixed-point FastICA algorithm; independent component analysis; mixture images; Biomedical signal processing; Computational intelligence; Covariance matrix; Geophysical signal processing; Independent component analysis; Laboratories; Pursuit algorithms; Signal processing algorithms; Source separation; Speech;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Security Workshops, 2007. CISW 2007. International Conference on
Conference_Location
Heilongjiang
Print_ISBN
978-0-7695-3073-4
Type
conf
DOI
10.1109/CISW.2007.4425489
Filename
4425489
Link To Document