%0 Journal Article
%T Vectorial total variation model for multi-channel SAR image denoising<br>多通道SAR图像滤波的向量总变分模型
%A Li Wen-Ping
%A Wang Zheng-Ming
%A Xie Mei-Hua
%A <br>李文屏
%A 王正明
%A 谢美华
%J 红外与毫米波学报
%D 2012
%I Science Press
%X This paper proposed an unsupervised technique for detecting changed areas between multitemporal SAR images. Different with the original ones, the clustering method was used here to find the change map by minimizing mean square error with evolution algorithm. After introducing the image character, a new search strategy in Memetic algorithm was given here, which adjusted the local search algorithm according to the current detection result. The approach was distribution free and did not need priori knowledge. The experimental results obtained on the real SAR images showed that the proposed method had a higher convergence speed than GA,ICSA and original MA, the detection results demonstrated the effectiveness of the proposed algorithm.
%K SAR images
%K change detection
%K Memetic algorithm<br>SAR图像
%K 变化检测
%K Memetic算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=D3B4F771D1A06062008B4D0A2EF05996&aid=4FBFB26F9F90CE2A330642C6D204CBE7&yid=99E9153A83D4CB11&vid=4AD960B5AD2D111A&iid=CA4FD0336C81A37A&sid=1D0FA33DA02ABACD&eid=5C3443B19473A746&journal_id=1001-9014&journal_name=红外与毫米波学报&referenced_num=0&reference_num=11