A new probabilistic image segmentation model based on hypothesis testing and Gibbs Random Fields is introduced. First, a probabilistic difference measure derived from a set of hyp...
In this paper we carry out cooperatively both disparity and object boundary estimation by setting the two tasks in a unified Markovian framework. We introduce a new joint probabil...
In contrast to traditional Markov random field (MRF) models, we develop a Steerable Random Field (SRF) in which the field potentials are defined in terms of filter responses that ...
A 3D super-resolution algorithm is proposed below, based on a probabilistic interpretation of the ndimensional version of Papoulis' generalized sampling theorem. The algorith...
Hassan Shekarforoush, Marc Berthod, Josiane Zerubi...
In this work we present Discriminative Random Fields (DRFs), a discriminative framework for the classification of image regions by incorporating neighborhood interactions in the l...