Independent Component Analysis by Using Joint Cumulants and its Application to Remote Sensing Images

被引：0
|
作者：
Xiaohui Zhang
C.H. Chen
机构：
[1] University of Massachusetts,Electrical and Computer Engineering Department
来源：
Journal of VLSI signal processing systems for signal, image and video technology | 2004年 / 37卷
关键词：
independent component analysis; joint cumulants; penalty function; gradient descent procedure; synthetic aperture radar images; comparison of algorithms;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, a joint cumulant independent component analysis (JC-ICA) algorithm is presented. It utilizes the higher order joint cumulants to extract independent components and can be implemented efficiently by a neural network. Its application in SAR (synthetic aperture radar) image analysis is presented and a comparison is also made with two other ICA methods. The results show the usage in image analysis and separation. Because the algorithm is based on statistics of order higher than the second, it is suitable also for applications to data with non-Gaussian distributions in blind signal processing.
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页码：293 / 303
页数：10
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