The MPM-MAP algorithm for image segmentation

We present a new algorithm for the efficient estimation of piecewise parametric models for image segmentation. This algorithm permits the simultaneous estimation of: the number of models; the parameters for each model and the regions where each model is applicable. It is based on Bayesian estimation theory, and is theoretically justified by the use of a specific cost function that decreases at every iteration and by a new model for the posterior marginal distributions which is amenable to the use of fast computational methods