PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Achim A., Kuruoglu E. E., Zerubia J. SAR image filtering based on the heavy-tailed rayleigh model. In: European Signal Processing conference (Antalya, Turkey, 4-8 september 2005). Proceedings, Suvisoft, 2005.
 
 
Abstract
(English)
We describe a novel adaptive despeckling filter for Synthetic Aperture Radar (SAR) images. In the proposed approach, the Radar Cross Section (RCS) is estimated using a maximum a posteriori (MAP) criterion. We first employ a logarithmic transformation to change the multiplicative speckle into additive noise. We model the RCS using the heavy-tailed Rayleigh distribution, which was recently proposed as an accurate model for amplitude SAR images. We estimate model parameters from noisy observations by applying the 'method-of-log-cumulants', which relies on the Mellin transform. Finally, we compare our proposed algorithm with the classical Lee filtering technique applied on an aerial image and we quantify the performance improvement.
Subject Synthetic aperture radar imaging
Alpha-stable distribution
Generalised (heavy-tailed) Rayleigh distribution
Log statistics
G.3 Probability and statistics. Distribution functions
G.3 Probability and statistics. Statistical computing


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