Mutually compatible Gibbs images: properties, simulation and identification

Presents a unified theory for the description of Gibbs images that allows one to answer some very important theoretical and practical questions about their statistical behavior. The author first introduces the local transfer function and derives the Gibbs measure in terms of this function. He restricts the derived probability structure to satisfy the property of mutual compatibility thus resulting in the subclass of mutually compatible Gibbs images. The author reviews their properties and briefly discusses various issues related to their simulation and identification. Simulation results from the area of texture analysis and synthesis are presented, in order to demonstrate various aspects of the theory