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Bayesian off-line detection of multiple change-points corrupted by multiplicative noise : application to SAR image edge detection

Tourneret, Jean-Yves and Doisy, Michel and Lavielle, Marc Bayesian off-line detection of multiple change-points corrupted by multiplicative noise : application to SAR image edge detection. (2003) Signal Processing, vol. 8 (n° 9). pp. 1871-1887. ISSN 0165-1684

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Official URL: http://dx.doi.org/10.1016/S0165-1684(03)00106-3

Abstract

This paper addresses the problem of Bayesian off-line change-point detection in synthetic aperture radar images. The minimum mean square error and maximum a posteriori estimators of the changepoint positions are studied. Both estimators cannot be implemented because of optimization or integration problems. A practical implementation using Markov chain Monte Carlo methods is proposed. This implementation requires a priori knowledge of the so-called hyperparameters. A hyperparameter estimation procedure is proposed that alleviates the requirement of knowing the values of the hyperparameters. Simulation results on synthetic signals and synthetic aperture radar images are presented.

Item Type:Article
Additional Information:This publication is available at http://www.sciencedirect.com/science/journal/01651684
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT
Université de Toulouse > Université Paul Sabatier-Toulouse III - UPS
Other partners > Université Paris-Sud 11 (FRANCE)
Laboratory name:
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Deposited By:Jean-yves TOURNERET

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