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 ...
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
In this paper we address the problem of simultaneous estimation of structure and restoration of images from blurred photometric measurements. Given the blurred observations of a s...
The notion of using context information for solving highlevel vision problems has been increasingly realized in the field. However, how to learn an effective and efficient context...
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...