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

نویسندگان

  • Kazuyuki Tanaka
  • Jun-ichi Inoue
چکیده

The framework is presented of Bayesian image restoration for multivalued images by means of the Q-Ising model with nearest-neighbor interactions. 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 gray-level images, the Q-Ising model can give us good results. PACS numbers: 02.50-r, 02.50.Cw, 02.50.Tt, 05.20.-y, 05.50.+q, 75.10.Nr, 89.70.+c § To whom correspondence should be addressed ([email protected]) Probabilistic image processing by the Q-Ising model 2

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تاریخ انتشار 2003