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, 8 (9). 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 |
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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 (FRANCE) Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE) Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE) Other partners > Université Paris-Sud 11 (FRANCE) |
Laboratory name: | Institut de Recherche en Informatique de Toulouse - IRIT (Toulouse, France) - Signal et Communication - SC |
Statistics: | download |
Deposited On: | 16 Sep 2009 13:33 |
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