DocumentCode
1316357
Title
Computational Bayesian analysis of hidden Markov mesh models
Author
Dunmur, A.P. ; Titterington, D.M.
Author_Institution
Dept. of Stat., Glasgow Univ., UK
Volume
19
Issue
11
fYear
1997
fDate
11/1/1997 12:00:00 AM
Firstpage
1296
Lastpage
1300
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;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.632989
Filename
632989
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