Despeckling SAR images in the undecimated wavelet domain: A MAP approach

被引：0

作者：

Argenti, F ^{[1
]}

Rovai, N ^{[1
]}

Alparone, L ^{[1
]}

机构：

[1] Univ Florence, Dipartimento Elettr & Telecomun, I-50139 Florence, Italy

来源：

2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING | 2005年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A method to despeckle SAR images based on the maximum a posteriori (MAP) estimation strategy in the undecimated wavelet domain is proposed. The method uses the assumption that the wavelet coefficients probability density functions (PDFs) are generalized Gaussians. The parameters of such distributions are computed by using the moments and the cumulants of the PDFs of the processes that constitute the SAR image, i.e., radar reflectivity and speckle noise. Experimental results demonstrate that the theory of MAP filtering can be successfully applied to SAR images represented in the shift-invariant wavelet domain.

引用

页码：541 / 544

页数：4

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