mrf2d: Markov random field image models in R

05/30/2020

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by   Victor Freguglia, et al.

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Markov random fields on two-dimensional lattices are behind many image analysis methodologies. mrf2d provides tools for a class of discrete stationary Markov random field models with pairwise interaction, which includes many of the popular models such as the Potts model and texture image models. The package introduces representations of dependence structures and parameters, visualization functions and efficient (C++ based) implementations of sampling algorithms, commom estimation methods and other key features of MRFs, providing a useful framework to implement algorithms and working with the model in general. This paper presents a description and details of the package, as well as some reproducible examples of usage.