Texture Segmentation of SAR Image Using Multires01utiOn Pairwise Markov Model

摘要：

A new method for segmentation of synthetic aperture radar(SAR)images is presented to consider spatial distributed characters between pixels of SAR images as well as the local means and variances statistics of gray level,a Gaussian autOregressive (GAR) modeI under a multiresolution pairwise Markov framework Based on texture feature images from gray level co-occurrence probability statistics,we examine the texture segmentation of SAR image suing the multi-resolution maximization of the posterior marginal(MPM)estimate with corresponding unsupervised segmentation algorithm on those texture feature images.For some SAR images.compared with multiresoiution pariwise Markov-GAR model texture segmentation based on gray Ievel images.the resuiIts of experimentation show that the proposed method in this paper has a better performance on segmentation precision.

关键词： SAR image Texture feature Pairwise Markov random field model Multiresolution MPM Texture segmentation

作者: Bao-li Liu

会议类型: 国际会议

会议名称: The International Conference Information Computing and Automation(2007国际信息计算与自动化会议)

会议地点: 成都

会议语种:英文

页码: 1348-1351

在线出版日期: 2007-12-19（万方平台首次上网日期，不代表论文的发表时间）