Introduction to Probabilistic Image Processing

Markov Random Field and Belief Propagation

Abstract

In this manuscript, we discuss Markov random fields and belief propagations, sum-product algorithm and max-product algorithm, that construct a framework of the probabilistic image processing. The concepts of these two topics have occupied an important place in the field of the computer vision. We see fundamental mathematics of probabilistic image processing from the viewpoint of Markov random fields and belief propagations, and see how to implement probabilistic image processing systems through an example of de-noising filter.