Bayesian off-line detection of multiple change-points corrupted by multiplicative noise : application to SAR image edge detection - Archive ouverte HAL Access content directly
Journal Articles Signal Processing Year : 2003

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

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.

Dates and versions

hal-03602985 , version 1 (09-03-2022)

Identifiers

Cite

Jean-Yves Tourneret, Michel Doisy, Marc Lavielle. Bayesian off-line detection of multiple change-points corrupted by multiplicative noise : application to SAR image edge detection. Signal Processing, 2003, 83 (9), pp.1871-1887. ⟨10.1016/S0165-1684(03)00106-3⟩. ⟨hal-03602985⟩
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