Title :
Computational Bayesian analysis of hidden Markov mesh models
Author :
Dunmur, A.P. ; Titterington, D.M.
Author_Institution :
Dept. of Stat., Glasgow Univ., UK
fDate :
11/1/1997 12:00:00 AM
Abstract :
Versions of the Gibbs sampler are derived for the analysis of data from the hidden Markov mesh random fields sometimes used in image analysis. This provides a numerical approach to the otherwise intractable Bayesian analysis of these problems. Detailed formulation is provided for particular examples based on Devijver´s Markov mesh model (1988), and the BUGS package is used to do the computations. Theoretical aspects are discussed and a numerical study, based on image analysis, is reported
Keywords :
Bayes methods; Markov processes; Monte Carlo methods; image sampling; BUGS package; Gibbs sampler; computational Bayesian analysis; hidden Markov mesh models; image analysis; numerical approach; Bayesian methods; Computational modeling; Data analysis; Degradation; Hidden Markov models; Image analysis; Image sampling; Monte Carlo methods; Packaging; Sampling methods;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
