MODEL

Neighbourhood-consensus message passing as a framework for generalized iterated conditional expectations

No-reference blur estimation based on the average cone ratio in the wavelet domain

With extensive technological advancements in electronic imaging today, high image quality is becoming an imperative necessity in the modern imaging systems. An important part of quality assurance are techniques for measuring the level of image …

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 …

Denoising of multicomponent images using wavelet least-squares estimators

Noise removal from images by projecting onto bases of principal components

In this paper, we develop a new wavelet domain statistical model for the removal of stationary noise in images. The new model is a combination of local linear projections onto bases of Principal Components, that perform a dimension reduction of the …

Estimating the probability of the presence of a signal of interest in multiresolution single- and multiband image denoising

We develop three novel wavelet domain denoising methods for subband-adaptive, spatially-adaptive and multivalued image denoising. The core of our approach is the estimation of the probability that a given coefficient contains a significant noise-free …