In this paper we propose an extension to the standard Markov Random Field (MRF) model in order to handle layers. Our extension, which we call a Factorial MRF (FMRF), is analogous t...
In this paper, we study unsupervised image segmentation using wavelet-domain hidden Markov models (HMMs). We first review recent supervised Bayesian image segmentation algorithms ...
Image segmentation algorithms partition the set of pixels of an image into a specific number of different, spatially homogeneous groups. We propose a nonparametric Bayesian model f...
Abstract. This paper presents a Bayesian inference algorithm for image layer representation [26], 2.1D sketch [6], with mixed Markov random field. 2.1D sketch is an very important...
In this work we introduce a probabilistic model for classifying segmented images. The proposed classifier is very general and it can deal both with images that were segmented wit...