Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images.

*(English)*Zbl 0573.62030Some methods for image restoration resulting by observing analogies between images and statistical lattice based systems are discussed. Their goal is to restore degraded images by means of a Bayesian approach introducing a statistical model based on the Gibbs distribution.

The problem of maximizing the conditional distribution of the image $X=(F,L)$ (F stands for the matrix of observable pixel intensities while L is a matrix of unobservable edge elements), given data $G=\underline{g}$, i.e. $P(X=\underline{x}|G=\underline{g})$ is solved with the aid of stochastic relaxation.

Reviewer: W.Pedrycz