Unsupervised Classification of PoISAR Data Using Freeman Decomposition and Fuzzy Clustering

摘要：

An unsupervised classification method using Freeman decomposition and fuzzy clustering is proposed to solve the ambiguity problem among surface,volume and double-bounce scattering dominated region. A fuzzy clustering method of PoISAR data making use of scattering power entropy and anisotropy paramters is proposed to partition different scattering mechanisms dominated region. The proposed method is applied to full polarimetric synthetic aperture radar data of Oberpfaffenhofen acquired by ESAR.Experiment result confirms the validity of this method.

关键词： PoISAR unsupervised classification Freeman decomposition fuzzy clustering

作者: Lulu Tan Ruliang Yang

作者单位: Institute of electronics,Chinese Academy of Sciences,China Graduate University of Chinese Academy of Institute of electronics,Chinese Academy of Sciences,China

会议类型: 国际会议

会议名称: 2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar(第二届亚太合成孔径雷达会议)

会议地点: 西安

会议语种:英文

页码: 489-493

在线出版日期: 2009-10-26（万方平台首次上网日期，不代表论文的发表时间）