Blind non-independent image separation based on independent component analysis

被引：0
|
作者：
Guo, Wu [1 ]
Zhang, Peng [1 ]
Wang, Runsheng [1 ]
机构：
[1] NUDT, ATR Lab, Changsha, Peoples R China
来源：
CIS WORKSHOPS 2007: INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY WORKSHOPS | 2007年
关键词：
D O I：
10.1109/CIS.Workshops.2007.170
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：271 / 274
页数：4
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