Diffused expectation maximisation for image segmentation

Diffused expectation maximisation is a novel algorithm for image segmentation. The method models an image as a finite mixture, where each mixture component corresponds to a region class and uses a maximum likelihood approach to estimate the parameters of each class, via the expectation maximisation algorithm, coupled with anisotropic diffusion on classes, in order to account for the spatial dependencies among pixels