Probabilistic image processing by means of the Bethe approximation for the Q-Ising model

Kazuyuki Tanaka, Jun Ichi Inoue, D. M. Titterington

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

The framework of Bayesian image restoration for multi-valued images by means of the Q-Ising model with nearest-neighbour interactions is presented. Hyperparameters in the probabilistic model are determined so as to maximize the marginal likelihood. A practical algorithm is described for multi-valued image restoration based on the Bethe approximation. The algorithm corresponds to loopy belief propagation in artificial intelligence. We conclude that, in real world grey-level images, the Q-Ising model can give us good results.

Original languageEnglish
Pages (from-to)11023-11035
Number of pages13
JournalJournal of Physics A: Mathematical and General
Volume36
Issue number43
DOIs
Publication statusPublished - 2003 Oct 31

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • Physics and Astronomy(all)

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