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

页码：726 / 737

页数：12

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