Title :
Bayesian TV denoising of SAR images
Author :
Vega, Miguel ; Mateos, Javier ; Molina, Rafael ; Katsaggelos, Aggelos K.
Author_Institution :
Dept. de Lenguajes y Sist. Informaticos, Univ. de Granada, Granada, Spain
Abstract :
Synthetic aperture radar (SAR) imagery suffers from the speckle phenomenon. Speckle gives rise to the presence of multiplicative noise which severely degrades the observed images. It is known that logarithmically transformed speckle can be well approximated by a Gaussian distribution. In this paper we propose an algorithm for despeckling images, within the log-transformed spatial domain, using a TV prior whose model parameter is automatically determined using the Evidence Analysis within the Hierarchical Bayesian Paradigm. The effectiveness of the proposed algorithm, over both synthetically speckled and real SAR images, is studied.
Keywords :
Bayes methods; Gaussian distribution; image denoising; radar imaging; speckle; synthetic aperture radar; Bayesian TV denoising; Gaussian distribution; SAR images; evidence analysis; hierarchical Bayesian paradigm; log transformed spatial domain; speckle phenomenon; synthetic aperture radar imagery; Algorithm design and analysis; Bayesian methods; Image restoration; Noise; Speckle; Synthetic aperture radar; TV; Bayesian methods; SAR images denoising; despeckling; image restoration; parameter estimation;
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2011.6115772