SAR image filtering based on the heavy-tailed rayleigh model
Achim A., Kuruoglu E. E., Zerubia J.
speckle noise Heavy-tailed Rayleigh distribution Computer Graphics and Computer-Aided Design SAR image [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH] ALPHA-STABLE DISTRIBUTIONS MELLIN TRANSFORM MAP ESTIMATION alpha stable distribution Statistical computing HEAVY-TAILED RAYLEIGH MODEL SYNTHETIC APERTURE RADAR Probability and statistics. Distribution functions Probability and statistics Software
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.
Source: IEEE transactions on image processing 15 (2006): 2686–2693. doi:10.1109/TIP.2006.877362
Publisher: Institute of Electrical and Electronics Engineers,, New York, NY , Stati Uniti d'America
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@article{oai:it.cnr:prodotti:43900,
title = {SAR image filtering based on the heavy-tailed rayleigh model},
author = {Achim A. and Kuruoglu E. E. and Zerubia J.},
publisher = {Institute of Electrical and Electronics Engineers,, New York, NY , Stati Uniti d'America},
doi = {10.1109/tip.2006.877362},
journal = {IEEE transactions on image processing},
volume = {15},
pages = {2686–2693},
year = {2006}
}
0000-0002-2608-8034
