HIERARCHICAL SEGMENTATION OF POLARIMETRIC SAR IMAGES USING HETEROGENEOUS CLUTTER MODELS

被引：3
|
作者：
Bombrun, L. [1 ]
Beaulieu, J-M.
Vasile, G. [1 ,2 ]
Ovarlez, J-P
Pascal, F. [2 ]
Gay, M. [1 ,2 ]
机构：
[1] CNRS Grenoble INP, Grenoble Image Speach Signal Automat Lab, Grenoble, France
[2] Grenoble Inst Technol, GIPSA Lab, F-38402 Grenoble, France
来源：
2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5 | 2009年
关键词：
Fisher PDF; KummerU PDF; PolSAR data; Segmentation; Spherically Invariant Random Vectors; COVARIANCE-MATRIX; ALGORITHM ANALYSIS; EXISTENCE; NOISE;
D O I：
10.1109/IGARSS.2009.5418271
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
In this paper, heterogeneous clutter models are introduced to describe Polarimetric Synthetic Aperture Radar (PolSAR) data. Based on the Spherically Invariant Random Vectors (SIRV) estimation scheme, the scalar texture parameter and the normalized covariance matrix are extracted. If the texture parameter is modeled by a Fisher PDF, the observed target scattering vector follows a KummerU PDF. Then, this PDF is implemented in a hierarchical segmentation algorithm. Segmentation results are shown on high resolution PolSAR data at L and X band.
引用
收藏
页码：1307 / +
页数：2
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