HETEROGENEOUS CLUTTER MODEL FOR HIGH RESOLUTION POLARIMETRIC SAR DATA PROCESSING

被引：1
|
作者：
Vasile, G. [1 ]
Pascal, F. [2 ]
Ovarlez, J. -P. [2 ,3 ]
Formont, P. [2 ]
机构：
[1] CNRS Grenoble INP, Grenoble Image SPeach Signal Automat Lab, F-38031 Grenoble, France
[2] SONDRA, Supelect, Grenoble, France
[3] ONERA DEMR TSI, French Aerosp Lab, Grenoble, France
来源：
2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2011年
关键词：
OPTIMAL SPECKLE REDUCTION; COVARIANCE-MATRIX; SPHERICALLY INVARIANT; CFAR DETECTION; IMAGERY; NOISE;
D O I：
10.1109/IGARSS.2011.6050039
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper presents a new estimation scheme for optimally deriving clutter parameters with high resolution POLSAR data. The heterogeneous clutter in POLSAR data is described by the Spherically Invariant Random Vectors model. Three parameters are introduced for the high resolution POLSAR data clutter: the span, the normalized texture and the speckle normalized covariance matrix. The asymptotic distribution of the novel span estimator is investigated. A novel heterogeneity test for the POLSAR clutter is also discussed. The proposed method is tested with airborne POLSAR images provided by the ONERA RAMSES system.
引用
收藏
页码：3744 / 3747
页数：4
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