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

Tanaka, K., Inoue, J. and Titterington, D.M. (2003) Probabilistic image processing by means of the Bethe approximation for the Q-Ising model. Journal of Physics A: Mathematical and General, 36, pp. 11023-11035. (doi:10.1088/0305-4470/36/43/025)

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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.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Titterington, Professor Michael
Authors: Tanaka, K., Inoue, J., and Titterington, D.M.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Journal of Physics A: Mathematical and General
Publisher:Institute of Physics Publishing Ltd.
ISSN:0305-4470

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