Two-Dimensional Discrete Gaussian Markov Random Field Models for Image Processing

This paper is concerned with a systematic exposition of the usefulness of two-dimensional (2-D) discrete Gaussian Markov random field (GMRF) models for image processing applications. Specifically, we discuss the following topics; notion of Markovianity on a plane, statistical inference in GMRF models, and their applications in several image related problems such as, image synthesis, texture classification, segmentation and image restoration.

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