Unsupervised classification using polarimetric decomposition and complex Wishart classifier

被引：12

作者：

Lee, JS ^{[1
]}

Grunes, MR ^{[1
]}

Ainsworth, TL ^{[1
]}

Du, L ^{[1
]}

Schuler, DL ^{[1
]}

Cloude, SR ^{[1
]}

机构：

[1] USN, Res Lab, Remote Sensing Div, Washington, DC 20375 USA

来源：

IGARSS '98 - 1998 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS 1-5: SENSING AND MANAGING THE ENVIRONMENT | 1998年

关键词：

D O I：

10.1109/IGARSS.1998.703778

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

In this paper, we propose a new method for unsupervised classification of terrain types and man-made objects using polarimetric SAR data. This technique is a combination of the unsupervised classification based on the polarimetric target decomposition (Cloude and Pottier, 1997) and the maximum likelihood classifier based on the complex Wishart distribution (Lee et at. 1994). The advantage of this approach is that clusters may be identified by the scattering mechanisms from the target decomposition. The effectiveness of this algorithm is demonstrated using JPL/AIRSAR and SIR-C polarimetric SAR images.

引用

页码：2178 / 2180

页数：3