We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Variational relaxations can be used to compute approximate minimizers of optimal partitioning and multiclass labeling problems on continuous domains. While the resulting relaxed co...
In this paper, we address the problem of color image restoration. Here, we model the image as a Markov Random Field (MRF) and propose a restoration algorithm in a multiresolution ...
P. K. Nanda, K. Sunil Kumar, S. Ghokale, Uday B. D...
Nowadays color image processing is an essential issue in computer vision. Variational formulations provide a framework for color image restoration, smoothing and segmentation prob...
Discrete tomography (DT) is concerned with the tomographic reconstruction of images that consist of only a small number of gray levels. DT reconstruction problems are usually unde...