709 citations · 4.7k across the 56 of their papers we have counts for
6 papers · 1 filter
A Bayesian Lower Bound for Parameter Estimation of Poisson Data Including Multiple Changes (extended)
Lucien Bacharach, Mohammed Nabil El Korso, Alexandre Renaux +1
This paper derives lower bounds for the mean square errors of parameter estimators in the case of Poisson distributed data subjected to multiple abrupt changes. Since both change l…
A Hierarchical Bayesian Model Accounting for Endmember Variability and Abrupt Spectral Changes to Unmix Multitemporal Hyperspectral Images
Pierre-Antoine Thouvenin, Nicolas Dobigeon, Jean-Yves Tourneret
Hyperspectral unmixing is a blind source separation problem which consists in estimating the reference spectral signatures contained in a hyperspectral image, as well as their rela…
EEG reconstruction and skull conductivity estimation using a Bayesian model promoting structured sparsity
Facundo Costa, Hadj Batatia, Thomas Oberlin +1
M/EEG source localization is an open research issue. To solve it, it is important to have good knowledge of several physical parameters to build a reliable head operator. Amongst t…
Unsupervised Nonlinear Spectral Unmixing based on a Multilinear Mixing Model
Qi Wei, Marcus Chen, Jean-Yves Tourneret +1
In the community of remote sensing, nonlinear mixing models have recently received particular attention in hyperspectral image processing. In this paper, we present a novel nonline…
R-FUSE: Robust Fast Fusion of Multi-Band Images Based on Solving a Sylvester Equation
Qi Wei, Nicolas Dobigeon, Jean-Yves Tourneret +2
This paper proposes a robust fast multi-band image fusion method to merge a high-spatial low-spectral resolution image and a low-spatial high-spectral resolution image. Following t…
Multi-Band Image Fusion Based on Spectral Unmixing
Qi Wei, Jose Bioucas-Dias, Nicolas Dobigeon +3
This paper presents a multi-band image fusion algorithm based on unsupervised spectral unmixing for combining a high-spatial low-spectral resolution image and a low-spatial high-sp…