%0 Journal Article
%T Texture feature fusion-based segmentation method of SAR images<br>一种基于纹理特征融合的SAR图像分割方法
%A LIU Bao-li
%A ZHAO Zong-tao
%A <br>刘保利
%A 赵宗涛
%J 计算机应用研究
%D 2011
%I 
%X This paper presented a new method for segmentation of synthetic aperture radar (SAR) images. It proposed a Gaussian autoregressive (GAR) model under a multiresolution pairwise Markov framework based on texture feature fusion images from in part gray level co-occurrence probability statistics, examined the texture segmentation of SAR image using the multi-resolution maximization of the posterior marginal (MPM) estimate with corresponding unsupervised segmentation algorithm on those texture feature fusion images. This method used the pixel gray level information, and also used pixel space location information, reduced the speckle noise effect for the segmentation. For some SAR images, compared with multiresolution pariwise Markov-GAR model texture segmentation based on gray level images, the results of experimentation show that the segmentation precision can be improved by the method in this paper.
%K 灰度共生矩阵
%K 特征融合
%K 双Markov模型
%K 多分辨MPM
%K 纹理分割
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=2EDE94D0B2FB7F12EF28519BF015752E&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=0B39A22176CE99FB&sid=895BB10EB8F3BD49&eid=3D8AB54CA690066A&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=13