ICA Based Speckle Filtering for Target Extraction in SAR Images Using Adaptive Space Separation  

作　　者：李昱彤 周越 杨磊 

机构地区：[1]Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University

出　　处：《Journal of Shanghai Jiaotong university(Science)》2008年第5期528-532,共5页上海交通大学学报（英文版）

基　　金：the National Natural Science Foundation of China (No. 60675023);the Aviation Science Foundation of China (No. 04F57004)

摘　　要：A novel approach based on independent component analysis (ICA) for speckle filtering and target extraction of synthetic aperture radar (SAR) images is proposed using adaptive space separation with weighted information entropy (WIE) incorporated. First the basis and the independent components are respectively obtained by ICA technique, and WIE of the image is computed; then based on the threshold computed from function T-WIE (threshold versus weighted-information-entropy), independent components are adaptively separated and the bases are classified accordingly. Thus, the image space is separated into two subspaces: "clean" and "noise". Then, a proposed nonlinear operator ABO is applied on each component of the 'clean' subspace for further optimization. Finally, recovery image is obtained reconstructing this subspace and target is easily extracted with binarisation. Note that here T-WIE is an interpolated function based on several representative target SAR images using proposed space separation algorithm.A novel approach based on independent component analysis （ICA） for speckle filtering and target extraction of synthetic aperture radar （SAR） images is proposed using adaptive space separation with weighted information entropy （WIE） incorporated. First the basis and the independent components are respectively obtained by ICA technique, and WIE of the image is computed; then based on the threshold computed from function T-WIE （threshold versus weighted-information-entropy）, independent components are adaptively sep- arated and the bases are classified accordingly. Thus, the image space is separated into two subspaces： ＂clean＂ and ＂noise＂. Then, a proposed nonlinear operator ABO is applied on each component of the ‘clean＇ subspace for further optimization. Finally, recovery image is obtained reconstructing this subspace and target is easily extracted with binarisation. Note that here T-WIE is an interpolated function based on several representative target SAR images using proposed space separation algorithm.

关 键 词：target extraction speckle filtering synthetic aperture radar （SAR） independent component analysis （ICA） adaptive space separation weighted information entropy （WIE） 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]