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 :
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