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: IEEE Transactions on Image Processing, vol. 15 (9) pp. 2686 - 2693. IEEE, 2006.
 
 
Abstract
(English)
Synthetic aperture radar (SAR) images are inherently affected by a signal dependent noise known as speckle, which is due to the radar wave coherence. In this paper, we propose a novel adaptive despeckling filter and derive a maximum a posteriori(MAP) estimator for the radar cross section (RCS). We first employ a logarithmic transformation to change the multiplicative speckle into additive noise. We model the RCS using the recently introduced heavy-tailed Rayleigh density function, which was derived based on the assumption that the real and imaginary parts of the received complex signal are best described using the alpha-stable family of distribution.We estimate model parameters from noisy observations by means of second-kind statistics theory, which relies on the Mellin transform. Finally, we compare the proposed algorithm with several classical speckle filters applied on actual SAR images. Experimental results show that the homomorphic MAP filter based on the heavy-tailed Rayleigh prior for the RCS is among the best for speckle removal.
URL: http://ieeexplore.ieee.org/iel5/83/35118/01673449.pdf?isnumber=35118&prod=JNL&a
Subject Heavy-tailed Rayleigh distribution
Generalised Rayleigh distribution
Alpha-stable distribution
Synthetic aperture radar
Speckle
I.4.10 Image Representation. Statistical
I.4.9 Image Processing and Computer Vision. Applications
G.3 Probability and statistics. Distribution functions


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