Probabilistic inference to the problem of inverse-halftoning based on statistical mechanics of the Q-Ising model

.On the basis of statistical mechanics of the Q-Ising model on the square lattice, we apply the maximizer of the posterior marginal (MPM) estimate to the problem of inverse-halftoning for halftone images generated by the probabilistic threshold mask method. Then, the Monte Carlo simulation clarifies that the MPM estimate achieves the same performance with the conventional linear filter if we use a free prior, and that the performance of the MPM estimate is improved if we appropriately set parameters of the model prior expressed by the Boltzmann factor of the Q-Ising model on the square lattice. Furthermore, we also find that the MPM estimate shows better performance in inner areas of the Bayer's arrays than on the boundaries.