SAR image filtering based on the heavy-tailed rayleigh model
Achim A., Kuruoglu E. E., Zerubia J.
Probability and statistics. Distribution functions Probability and statistics Statistical computing
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.
Source: 13th European Signal Processing conference, Antalya, 4-8 september 2005
Publisher: Suvisoft Oy Ltd, Tampere, FIN
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@inproceedings{oai:it.cnr:prodotti:91242,
title = {SAR image filtering based on the heavy-tailed rayleigh model},
author = {Achim A. and Kuruoglu E. E. and Zerubia J.},
publisher = {Suvisoft Oy Ltd, Tampere, FIN},
booktitle = {13th European Signal Processing conference, Antalya, 4-8 september 2005},
year = {2005}
}
0000-0002-2608-8034