Markov Random Field

A two stage patch-based Markov Random Field approach to structure-aware image inpainting

Depth-guided patch-based disocclusion filling for view synthesis via Markov random field modelling

In this paper, we propose a novel patch-based disocclusion filling method for view synthesis from video-plus-depth data. The proposed method treats disocclusion filling as a global optimization problem, where global (spatial) consistency among the …

On structured sparsity and selected applications in tomographic imaging

This work explores the potentials of structure encoding in sparse tomographic reconstructions. We are encoding spatial structure with Markov Random Field (MRF) models and employ it within Magnetic Resonance Imaging (MRI) and Quantitative Microwave …

Single image example-based super-resolution using cross-scale patch matching and Markov random field modelling

Example-based super-resolution has become increasingly popular over the last few years for its ability to overcome the limitations of classical multi-frame approach. In this paper we present a new example-based method that uses the input …

A joint inter- and intrascale statistical model for Bayesian wavelet based image denoising

This paper presents a new wavelet-based image denoising method, which extends a recently emerged textacutedblgeometricaltextacutedbl Bayesian framework. The new method combines three criteria for distinguishing supposedly useful coefficients from …