We consider the problem of image deconvolution. We foccus on a Bayesian approach which consists of maximizing an energy obtained by a Markov Random Field modeling. MRFs are classi...
Abstract--This paper presents a new wavelet-based image denoising method, which extends a recently emerged "geometrical" Bayesian framework. The new method combines three...
Aleksandra Pizurica, Wilfried Philips, Ignace Lema...
We develop a Bayesian model of digitized archival films and use this for denoising, or more specifically de-graining, individual frames. In contrast to previous approaches our mod...
Teodor Mihai Moldovan, Stefan Roth, Michael J. Bla...
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
We propose an algorithm for estimating disparity and occlusion in stereo video sequences. The algorithm defines a prior on sequences of disparity maps using a 3D Markov random fie...
Oliver M. C. Williams, Michael Isard, John MacCorm...