Multiscale MAP filtering of SAR images

Author

Foucher, Samuel ; Bénié, Goze Bertin ; Boucher, Jean-Marc

Author_Institution

Centre d´´Applications et de Recherche en Teledetection, Sherbrooke Univ., Que., Canada

Volume

10

Issue

1

fYear

2001

fDate

1/1/2001 12:00:00 AM

Firstpage

49

Lastpage

60

Abstract

Synthetic aperture radar (SAR) images are disturbed by a multiplicative noise depending on the signal (the ground reflectivity) due to the radar wave coherence. Images have a strong variability from one pixel to another reducing essentially the efficiency of the algorithms of detection and classification. We propose to filter this noise with a multiresolution analysis of the image. The wavelet coefficient of the reflectivity is estimated with a Bayesian model, maximizing the a posteriori probability density function. The different probability density function are modeled with the Pearson system of distributions. The resulting filter combines the classical adaptive approach with wavelet decomposition where the local variance of high-frequency images is used in order to segment and filter wavelet coefficients

Keywords

Bayes methods; adaptive filters; filtering theory; image classification; image resolution; noise; probability; radar detection; radar imaging; synthetic aperture radar; wavelet transforms; Bayesian model; Pearson system; SAR images; a posteriori probability density function; adaptive filter; filter wavelet coefficients; ground reflectivity; high-frequency images; image multiresolution analysis; local variance; multiplicative noise; multiscale MAP filtering; radar wave coherence; synthetic aperture radar; wavelet coefficient; wavelet decomposition; Adaptive filters; Coherence; Filtering; Pixel; Probability density function; Radar detection; Radar imaging; Reflectivity; Synthetic aperture radar; Wavelet coefficients;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.892442

Filename

892442