Synchronous Random Fields and Image Restoration

Synchronous Image restoration

We utilize in this work a new class of random fields on some given set of sites, which are invariant under the action of a transit ion probability which synchronously updates the states of all sites. We illustrate, with an issue of image restoration, the usefulness of these models, and their feasibility for practical applications. We begin by a summary of the definition of p-periodic synchronou...

A Comparative Study of Some Markov Random Fields and Different Criteria Optimization in Image Restoration

Compound Gauss-markov Random Fields for Astronomical Image Restoration

Over the last few years, a growing number of researchers from varied disciplines have been utilizing Markov random fields (MRF) models for developing optimal, robust algorithms for various problems, such as texture analysis, image synthesis, image restoration, classification and segmentation, surface reconstruction, integration of several low level vision modules and sensor fusion. While linear...

Bayesian multichannel image restoration using compound Gauss-Markov random fields

In this paper, we develop a multichannel image restoration algorithm using compound Gauss-Markov random fields (CGMRF) models. The line process in the CGMRF allows the channels to share important information regarding the objects present in the scene. In order to estimate the underlying multichannel image, two new iterative algorithms are presented and their convergence is established. They can...

Primal-dual Algorithm for Convex Markov Random Fields

Computing maximum a posteriori configuration in a first-order Markov Random Field has become a routinely used approach in computer vision. It is equivalent to minimizing an energy function of discrete variables. In this paper we consider a subclass of minimization problems in which unary and pairwise terms of the energy function are convex. Such problems arise in many vision applications includ...