%0 Journal Article
%T SAR image despeckling: based on non-local means with non-subsample Shearlet and directional windows<br>基于非下采样Shearlet和方向权值邻域窗的非局部均值SAR图像相干斑抑制
%A ZHANG Xiao-Hu
%A CHEN Jia-Wei
%A MENG Hong-Yun
%A JIAO Li-Cheng
%A SUN Xiang
%A <br>张小华
%A 陈佳伟
%A 孟红云
%A 焦李成
%A 孙翔
%J 红外与毫米波学报
%D 2012
%I Science Press
%X Good performance has been obtained by extending traditional image denoising algorithm from local computation model to non-local one with non-local means algorithm. For synthesis aperture radar (SAR) image, however, the similarity measured by observations and isotropic window is not robust and without direction, which is bad for capturing the structure of image. In this paper, Non-subsample Shearlet feature and directional neighborhood based non-local means algorithm are proposed. Experimental results demonstrated that the improved non-local means algorithm can not only remove the speckle, but also preserve the geometrical structure information which is essential for understanding and interpretation of SAR image.
%K 非局部均值
%K 非下采样Shearlet特征描述子
%K 方向邻域窗
%K SAR图像降斑
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=D3B4F771D1A06062008B4D0A2EF05996&aid=74742B36888D8316B971F5F60CE73FB0&yid=99E9153A83D4CB11&vid=4AD960B5AD2D111A&iid=0B39A22176CE99FB&sid=BA79719BCA7341D5&eid=31611641D4BB139F&journal_id=1001-9014&journal_name=红外与毫米波学报&referenced_num=0&reference_num=23