MAXIMUM A POSTERIORI ESTIMATION OF RADAR CROSS SECTION IN SAR IMAGES USING THE HEAVY-TAILED RAYLEIGH MODEL (WedAmOR4)

Author(s) : Alin Achim (University of Bristol, United Kingdom) Ercan E. Kuruoglu (ISTI-CNR, Italy) Josiane Zerubia (INRIA, France)

Abstract : 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 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.

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