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SAR Image Filtering Based on the Heavy-Tailed Rayleigh Model

Alin Achim 1 Ercan E. Kuruoglu 1 Josiane Zerubia 1 
1 ARIANA - Inverse problems in earth monitoring
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SIS - Signal, Images et Systèmes
Abstract : 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 report, 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 our 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.
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Submitted on : Friday, May 19, 2006 - 8:44:00 PM
Last modification on : Saturday, June 25, 2022 - 10:56:43 PM
Long-term archiving on: : Tuesday, February 22, 2011 - 11:45:10 AM

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Alin Achim, Ercan E. Kuruoglu, Josiane Zerubia. SAR Image Filtering Based on the Heavy-Tailed Rayleigh Model. [Research Report] RR-5493, INRIA. 2006, pp.21. ⟨inria-00070514⟩

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