%0 Journal Article
%T Unsupervised Classification of Polarimetric SAR Image Using Deorientation Theory and Complex Wishart Distribution<br>基于去取向理论的全极化SAR图像模糊非监督聚类
%A Kang Xin
%A Han Chong-zhao
%A Xu Feng
%A Wang Ying-hua
%A <br>康欣
%A 韩崇昭
%A 徐丰
%A 王英华
%J 电子与信息学报
%D 2007
%I 
%X Scatter targets of complex terrain surfaces with random orientation product random fluctuating echoes. This leads to a confused classification by directly using target decomposition on full polarimetric SAR (PolSAR) image. To solve this problem, a new unsupervised classification method is proposed in this paper. Firstly, the target vector is transformed to the state with minimization of cross-polarization (min-x-pol); then the parameters u/v/H are used to characterized scattering mechanism, and the fuzzy membership is adopted instead of "hard" division of parameter plan; finally, characterizing the coherency matrix as multivariable complex Wishart distribution, the polarimetric SAR image is classified based on Bayes maximum likelihood criteria. Experiment is performed on a L-band NASA/JPL SIR-C polarimetric SAR image over Danshui town, Guangdong, P.R. China. Furthermore, the movements of the clustering centers are discussed. Compared with the k-mean like method based on , the results show that the proposed method provides a significant performance improvement in classification result and the associated scattering mechanism of class is more accurate. The classification result is beneficial for automatic recognition of terrain type.
%K Synthetic Aperture Radar (SAR)
%K Deorientation
%K Unsupervised classification
%K Fuzzy clustering
%K Radar polarimetry<br>合成孔径雷达
%K 去取向
%K 无监督分类
%K 模糊聚类
%K 雷达极化
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=C081889E519CA9E1&yid=A732AF04DDA03BB3&vid=771469D9D58C34FF&iid=E158A972A605785F&sid=F7C11D7E3E8C5D3F&eid=4C69616AE50D2DDC&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=0&reference_num=18