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

Author

Argenti, Fabrizio ; Rovai, Nicola ; Alparone, Luciano

Author_Institution

Dept. of Electron. & Telecommun., Univ. of Florence, Italy

Volume

4

fYear

2005

fDate

18-23 March 2005

Abstract

A method to despeckle SAR images based on a maximum a posteriori (MAP) estimation strategy in the undecimated wavelet domain is proposed. The method uses the assumption that the wavelet coefficient 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.

Keywords

Gaussian distribution; filtering theory; higher order statistics; image denoising; maximum likelihood estimation; radar imaging; speckle; synthetic aperture radar; wavelet transforms; MAP estimation; MAP filtering theory; SAR image despeckling; cumulants; generalized Gaussian distribution; maximum a posteriori estimation; moments; radar reflectivity; speckle noise; undecimated wavelet domain; wavelet coefficient probability density functions; Distributed computing; Filtering theory; Gaussian processes; Probability density function; Radar imaging; Reflectivity; Speckle; Synthetic aperture radar; Wavelet coefficients; Wavelet domain;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on

ISSN

1520-6149

Print_ISBN

0-7803-8874-7

Type

conf

DOI

10.1109/ICASSP.2005.1416065

Filename

1416065