Bayesian image and pattern reconstruction from incomplete and noisy data

Abstract

A Bayesian iterative method can be the basis for a wide range of technologies in the field of pattern recognition and image reconstruction. It involves finding the most probable solutions for images or patterns, if functionals describing the likelihood function and a priori information, respectively, are already known. The article describes the basic principles and recent advances in the development of BIM and its applications in various fields, mainly in tomography and restoration of functions from incomplete and noisy data.Keywords: image and pattern restoration, iterative methods, Bayes method, maximum entropy method, a pri ori information, Gibbs energy.