Segmentation of multilevel images using Gibbs distribution

An algorithm for multilevel image segmentation is presented. The main feature is that it is based on repetition of a binary segmentation algorithm, in a fashion similar to the binary expansion of an integer number. The binary segmentation considered assumes a Markov Random Field model for the original scene, and an additive i.i.d, noise signal. Simulation rasults are presented, and compared with other filtering algorithms, such as median filtering.