Probabilistic image processing by means of the Bethe approximation for theQ-Ising model
Kazuyuki Tanaka, Jun-ichi Inoue, D. Michael Titterington · Journal of Physics A Mathematical and General · 2003
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.