DocumentCode :
2942208
Title :
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
Link To Document :
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