387 citations · 600 across the 6 of their papers we have counts for
6 papers
Local-mean preserving post-processing step for non-negativity enforcement in PET imaging: application to Y-PET
Maël Millardet, Saïd Moussaoui, Diana Mateus +2
In a low-statistics PET imaging context, the positive bias in regions of low activity is a burning issue. To overcome this problem, algorithms without the built-in non-negativity c…
Sub-micron spatial resolution in far-field Raman imaging via positivity constrained super-resolution
Dominik J. Winterauer, Daniel Funes-Hernando, Jean-Luc Duvail +3
Raman microscopy is a valuable tool for detecting physical and chemical properties of a sample material. When probing nanomaterials or nanocomposites the spatial resolution of Rama…
Efficient Gaussian Sampling for Solving Large-Scale Inverse Problems using MCMC Methods
Clément Gilavert, Saïd Moussaoui, Jérôme Idier
The resolution of many large-scale inverse problems using MCMC methods requires a step of drawing samples from a high dimensional Gaussian distribution. While direct Gaussian sampl…
Implementation strategies for hyperspectral unmixing using Bayesian source separation
Frederic Schmidt, Albrecht Schmidt, Erwan Treguier +3
Bayesian Positive Source Separation (BPSS) is a useful unsupervised approach for hyperspectral data unmixing, where numerical non-negativity of spectra and abundances has to be ens…
Bayesian separation of spectral sources under non-negativity and full additivity constraints
Nicolas Dobigeon, Said Moussaoui, Jean-Yves Tourneret +1
This paper addresses the problem of separating spectral sources which are linearly mixed with unknown proportions. The main difficulty of the problem is to ensure the full additivi…
Joint Bayesian endmember extraction and linear unmixing for hyperspectral imagery
Nicolas Dobigeon, Said Moussaoui, Martial Coulon +2
This paper studies a fully Bayesian algorithm for endmember extraction and abundance estimation for hyperspectral imagery. Each pixel of the hyperspectral image is decomposed as a…