This paper aims to solve the problem of Blind Signal Separation (BSS) in a convolutive environment based on output correlation matrix diagonalization. Firstly an extension of the ...
We propose a new image and blur prior model, based on nonstationary autoregressive (AR) models, and use these to blindly deconvolve blurred photographic images, using the Gibbs sa...
We investigate a hybrid method which improves the quality of state inference and parameter estimation in blind deconvolution of a sparse source modeled by a Bernoulli-Gaussian pro...
Sparsity constraints are now very popular to regularized inverse problems. We review several approaches which have been proposed in the last ten years to solve inverse problems su...
Functional properties of living tissues appear in PET, whereas structural information at significantly higher resolution and better image quality is provided by other modalities, ...