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

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

研究成果: Article査読

23 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)11023-11035
ページ数13
ジャーナルJournal of Physics A: Mathematical and General
36
43
DOI
出版ステータスPublished - 2003 10月 31

ASJC Scopus subject areas

  • 統計物理学および非線形物理学
  • 数理物理学
  • 物理学および天文学(全般)

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