Hierarchical Segmentation of Polarimetric SAR Images Using Heterogeneous Clutter Models

被引：72
|
作者：
Bombrun, Lionel [1 ,2 ]
Vasile, Gabriel [3 ]
Gay, Michel [3 ]
Totir, Felix [3 ]
机构：
[1] Grenoble Inst Technol, Grenoble Image SPeech Signal Automat Lab GIPSA La, Grenoble Inst Technol, F-38402 Grenoble, France
[2] DSTA Res Alliance SONDRA, Supelec, ONERA, NUS, F-91192 Gif Sur Yvette, France
[3] Grenoble Inst Technol, GIPSA Lab, F-38402 Grenoble, France
来源：
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2011年 / 49卷 / 02期
关键词：
Fisher probability density function (PDF); KummerU PDF; polarimetric synthetic aperture radar (PolSAR) data; segmentation; spherically invariant random vectors (SIRV); COVARIANCE-MATRIX; CLASSIFICATION; DECOMPOSITION; EXISTENCE;
D O I：
10.1109/TGRS.2010.2060730
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, heterogeneous clutter models are used to describe polarimetric synthetic aperture radar (PolSAR) data. The KummerU distribution is introduced to model the PolSAR clutter. Then, a detailed analysis is carried out to evaluate the potential of this new multivariate distribution. It is implemented in a hierarchical maximum likelihood segmentation algorithm. The segmentation results are shown on both synthetic and high-resolution PolSAR data at the X- and L-bands. Finally, some methods are examined to determine automatically the "optimal" number of segments in the final partition.
引用
收藏
页码：726 / 737
页数：12
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