Title :
Bayesian estimation of abrupt changes contaminated by multiplicative noise using MCMC
Author :
Tourneret, Jean-Yves ; Doisy, Michel ; Mazzei, Manuel
Author_Institution :
ENSEIHT/GAPSE, Nat. Polytech. Inst. of Toulouse, France
Abstract :
The paper addresses the estimation of abrupt changes which are contaminated by multiplicative Gaussian noise. The marginal mean a posteriori or marginal maximum a posteriori estimators can be derived for estimating the position of a single abrupt change. However, these estimators have optimization or integration problems for multiple abrupt changes. The paper solves these optimization problems by using Markov chain Monte Carlo methods (MCMC)
Keywords :
Bayes methods; Gaussian noise; Markov processes; Monte Carlo methods; maximum likelihood estimation; parameter estimation; radar detection; radar imaging; spectral analysis; synthetic aperture radar; white noise; Bayesian estimation; MCMC; Markov chain Monte Carlo methods; SAR image processing; abrupt change estimation; integration problem; marginal maximum a posteriori estimator; marginal mean a posteriori estimator; multiplicative white Gaussian noise; optimization problem; position estimation; spectral analysis algorithm; Bayesian methods; Gaussian noise; Image processing; Maximum a posteriori estimation; Maximum likelihood estimation; Optimization methods; Reflectivity; Signal processing; Speckle; Synthetic aperture radar;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.681567
