Unsupervised Polarimetric SAR Image Classification using Fisher linear discriminant

摘要：

How to use the POLSAR data to classify and interpret the conditions of the earth is a very important research field of POLSAR.In this paper,we propose an improved algorithm on the basis of studying and analyzing some common algorithms. This technique introduces the fisher criterion in the feature selection and the hierarchical method in the classification of POLSAR image,which can improve Lees combination method of the unsupervised classification based on polarimetric target decomposition and the maximum likelihood classifier based on the complex Wishart distribution. The effectiveness of this algorithm is demonstrated using a polerimetric SAR image.

关键词： Radar polarimetry synthetic aperture radar feature selection terrain classification

作者: Bo Chen Shuang Wang Licheng Jiao Shuang Zhang

作者单位: Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China,Institute of Intelligent Information Processing,Xidian University,Xian 710071,P.R.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: 738-741

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）