%0 Journal Article
%T AUTOMATIC MULTIRESOLUTION CLASSIFICATION OF POLARIMETRIC SAR IMAGE WITH WAVELET TRANSFORM AND MARKOV RANDOM FIELD<br>基于小波变换和马尔可夫随机场的极化SAR图像自动分类
%A Liu Guoqing
%A Xiong Hong
%A Huang Shunji
%A <br>刘国庆
%A 熊红
%A 黄顺吉
%J 电子与信息学报
%D 2000
%I 
%X In this paper an automatic multiresolution classification method is proposed to classify polarimetric synthetic aperture radar (SAR) image.At first a textured SAR image characterizing the terrain reflection is obtained by using a multi-look polarimetric whitening filter (MPWF) to reduce the speckle in the polarimetric SAR image. Then the wavelet transform (WT) is utilized to extract texture information in different resolutions, and in the lowest resolution level the Akaik information criterion (AIC) is used for estimating the optimal number of texture classes in the image. Next the Markov random field (MRF) model is employed to characterize the spatial constraints between pixels in each resolution level, and a maximum likelihood (ML) approach and an iterated conditional mode (ICM) approach are used for the model parameters estimation and maximum a posteriori (MAP) classification, respectively. Finally the paper presents the experimental results with the NASA/JPL L-band airborne polarimetric SAR data and verifies the effectiveness and advantage of the classification method proposed.
%K Polarimetric synthetic aperture radar (SAR)
%K Multiresolution
%K Classification
%K Wavelet transform (WT)
%K Markov random field (MRF)
%K Maximum a posteriori (MAP)<br>极化合成孔径雷达(SAR)
%K 多分辨率
%K 分类
%K 小波变换(WT)
%K 马尔可夫随机场(MRF)
%K 最大后验概率(MAP)
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=024ED7AAB6954CABA6AC5EC5D390CC10&yid=9806D0D4EAA9BED3&vid=BC12EA701C895178&iid=38B194292C032A66&sid=3356A7630A93A219&eid=683005D16807E4FE&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=0&reference_num=13