Classification With a Non-Gaussian Model for PolSAR Data

被引:112
作者
Doulgeris, Anthony P. [1 ]
Anfinsen, Stian Normann [1 ]
Eltoft, Torbjorn [1 ]
机构
[1] Univ Tromso, Dept Phys & Technol, N-9037 Tromso, Norway
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2008年 / 46卷 / 10期
关键词
Image classification; K-distribution; non-Gaussian statistics; polarimetric synthetic aperture radar (PolSAR); scale mixture of Gaussian (SMoG); Wishart distribution;
D O I
10.1109/TGRS.2008.923025
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
In this paper, we present a generalized Wishart classifier derived from a non-Gaussian model for polarimetric synthetic aperture radar (PolSAR) data. Our starting point is to demonstrate that the scale mixture of Gaussian (SMoG) distribution model is suitable for modeling PolSAR data. We show that the distribution of the sample covariance matrix for the SMoG model is given as a generalization of the Wishart distribution and present this expression in integral form. We then derive the closed-form solution for one particular SMoG distribution, which is known as the multivariate K-distribution. Based on this new distribution for the sample covariance matrix, termed as the K-Wishart distribution, we propose a Bayesian classification scheme, which can be used in both supervised and unsupervised modes. To demonstrate the effect of including non-Gaussianity, we present a detailed comparison with the standard Wishart classifier using airborne EMISAR data.
引用
收藏
页码:2999 / 3009
页数:11
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