标题:An Unsupervised Scattering Mechanism Classification Method for PolSAR Images

作者:Cheng, XG (Cheng, Xiaoguang); Huang, WL (Huang, Wenli); Gong, JY (Gong, Jianya)

来源出版物:IEEE GEOSCIENCE AND REMOTE SENSING LETTERS卷:11期:10页:1677-1681DOI:10.1109/LGRS.2014.2305655出版年:OCT 2014

Web of Science 核心合集中的 "被引频次":1

被引频次合计:1

摘要:This letter concentrates on scattering mechanism classification of polarimetric synthetic aperture radar (Po1SAR) images. Scattering mechanism classes are defined as the combinations of dominant and secondary scattering mechanisms. With three metrics extracted from the observed coherency matrix, an unsupervised classifier is proposed to classify PolSAR pixels into eight combinations of surface scattering, double- bounce scattering, and volume scattering. When applying the proposed method to simulated data, the Kappa coefficient is 0.891. It effectively classifies the dominant mechanism, and the Kappa coefficient is 0.127 higher than that of the H/alpha method. Experiment using uninhabited aerial vehicle SAR data shows that the proposed method is able to identify secondary mechanism in forests and urban areas. This method is not only a good classifier free of specific polarimetric decomposition but also can serve as a pre-classification step of sophisticated classification scheme.

地址：[Cheng, Xiaoguang; Gong, Jianya] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China.

[Huang, Wenli] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA.

通讯作者地址:Cheng, XG (通讯作者),Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China.

电子邮件地址:shenjianzi.cheng@gmail.com