Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/47613
Title: Supervised evolutionary optimization of Bayesian nonlocal means filter with sigma preselection for despeckling sar images
Authors: Gomez, Luis 
Munteanu, Cristian
Buemi, Maria
Berlles, Julio Jacobo
Mejail, Marta
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
Keywords: Bayesian methods
Speckle
Noise measurement
Synthetic aperture radar
Genetic algorithms
Issue Date: 2012
Journal: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR 
Conference: 9th European Conference on Synthetic Aperture Radar, EUSAR 2012 
Abstract: Speckle reduction is an important problem in SAR image analysis. We present an interactive easy-To-use software package based on an evolutionary algorithm, to optimize a despeckling Bayesian nonlocal means filter with sigma preselection for reducing the image variance while preserving the image mean. As a difference from other methodologies, there is an implication of the user, which provides a subjective validation to complete the Bayesian filter design. We apply the methodology on both synthetic and real intensity SAR images and the results show the effectiveness of the proposal.
URI: http://hdl.handle.net/10553/47613
ISBN: 9783800734047
ISSN: 2197-4403
Source: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR[ISSN 2197-4403],v. 2012-April (06217189), p. 788-791
Appears in Collections:Actas de congresos
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