Segmentation of Images for Environmental Studies Using a Simple Markov/Gibbs Random Field Model.

A novel probabilistic model of noisy piecewise-constant images is used to segment real images being of interest for ecological monitoring. The model considers a pair composed of a greyscale (or multiband) image and a map of its homogeneous regions as a sample of a Markov random field (MRF) specified by a joint Gibbs probability distribution (GPD) of images and maps. Parameters of the model are estimated by using a stochastic approximation technique. Here, its convergence to the desired values is studied experimentally.