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Computational Bayesian analysis of hidden Markov mesh models

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2 Author(s)
Dunmur, A.P. ; Dept. of Stat., Glasgow Univ., UK ; Titterington, D.M.

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

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:19 ,  Issue: 11 )

Date of Publication:

Nov 1997

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