research
∙
07/01/2023
AE-RED: A Hyperspectral Unmixing Framework Powered by Deep Autoencoder and Regularization by Denoising
Spectral unmixing has been extensively studied with a variety of methods...
share
research
∙
06/29/2023
Guided Deep Generative Model-based Spatial Regularization for Multiband Imaging Inverse Problems
When adopting a model-based formulation, solving inverse problems encoun...
research
∙
05/20/2023
Normalizing flow sampling with Langevin dynamics in the latent space
Normalizing flows (NF) use a continuous generator to map a simple latent...
research
∙
04/21/2023
Plug-and-Play split Gibbs sampler: embedding deep generative priors in Bayesian inference
This paper introduces a stochastic plug-and-play (PnP) sampling algorith...
research
∙
07/12/2022
Sliced-Wasserstein normalizing flows: beyond maximum likelihood training
Despite their advantages, normalizing flows generally suffer from severa...
research
∙
07/04/2022
Learning Optimal Transport Between two Empirical Distributions with Normalizing Flows
Optimal transport (OT) provides effective tools for comparing and mappin...
research
∙
03/02/2022
CD-GAN: a robust fusion-based generative adversarial network for unsupervised change detection between heterogeneous images
In the context of Earth observation, the detection of changes is perform...
research
∙
11/24/2020
Provably robust blind source separation of linear-quadratic near-separable mixtures
In this work, we consider the problem of blind source separation (BSS) b...
research
∙
10/04/2020
High-dimensional Gaussian sampling: a review and a unifying approach based on a stochastic proximal point algorithm
Efficient sampling from a high-dimensional Gaussian distribution is an o...
research
∙
02/04/2020
Fast reconstruction of atomic-scale STEM-EELS images from sparse sampling
This paper discusses the reconstruction of partially sampled spectrum-im...
research
∙
12/26/2019
Hyperspectral and multispectral image fusion under spectrally varying spatial blurs – Application to high dimensional infrared astronomical imaging
Hyperspectral imaging has become a significant source of valuable data f...
research
∙
07/19/2019
Matrix cofactorization for joint spatial-spectral unmixing of hyperspectral images
Hyperspectral unmixing aims at identifying a set of elementary spectra a...
research
∙
02/15/2019
Asymptotically exact data augmentation: models, properties and algorithms
Data augmentation, by the introduction of auxiliary variables, has becom...
research
∙
02/07/2019
Matrix Cofactorization for Joint Representation Learning and Supervised Classification -- Application to Hyperspectral Image Analysis
Supervised classification and representation learning are two widely use...
research
∙
07/30/2018
Factor analysis of dynamic PET images: beyond Gaussian noise
Factor analysis has proven to be a relevant tool for extracting tissue t...
research
∙
07/21/2018
Coupled dictionary learning for unsupervised change detection between multi-sensor remote sensing images
Archetypal scenarios for change detection generally consider two images ...
research
∙
04/30/2018
Hyperspectral unmixing with spectral variability using adaptive bundles and double sparsity
Spectral variability is one of the major issue when conducting hyperspec...
research
∙
04/16/2018
Split-and-augmented Gibbs sampler - Application to large-scale inference problems
Recently, a new class of Markov chain Monte Carlo (MCMC) algorithms took...
research
∙
04/09/2018
Robust fusion algorithms for unsupervised change detection between multi-band optical images - A comprehensive case study
Unsupervised change detection techniques are generally constrained to tw...
research
∙
02/27/2018
Reconstruction of partially sampled multi-band images - Application to STEM-EELS imaging
Electron microscopy has shown to be a very powerful tool to map the chem...
research
∙
12/01/2017
Hierarchical Bayesian image analysis: from low-level modeling to robust supervised learning
Within a supervised classification framework, labeled data are used to l...
research
∙
09/17/2017
Bayesian nonparametric Principal Component Analysis
Principal component analysis (PCA) is very popular to perform dimension ...
research
∙
07/19/2017
Unmixing dynamic PET images with variable specific binding kinetics
To analyze dynamic positron emission tomography (PET) images, various ge...
research
∙
09/20/2016
Robust Fusion of Multi-Band Images with Different Spatial and Spectral Resolutions for Change Detection
Archetypal scenarios for change detection generally consider two images ...
research
∙
09/20/2016
Detecting Changes Between Optical Images of Different Spatial and Spectral Resolutions: a Fusion-Based Approach
Change detection is one of the most challenging issues when analyzing re...
research
∙
08/27/2016
Bayesian selection for the l2-Potts model regularization parameter: 1D piecewise constant signal denoising
Piecewise constant denoising can be solved either by deterministic optim...
research
∙
04/06/2016
R-FUSE: Robust Fast Fusion of Multi-Band Images Based on Solving a Sylvester Equation
This paper proposes a robust fast multi-band image fusion method to merg...
research
∙
03/29/2016
Multi-Band Image Fusion Based on Spectral Unmixing
This paper presents a multi-band image fusion algorithm based on unsuper...
research
∙
12/18/2015
Bayesian anti-sparse coding
Sparse representations have proven their efficiency in solving a wide cl...
research
∙
10/20/2015
Online Unmixing of Multitemporal Hyperspectral Images accounting for Spectral Variability
Hyperspectral unmixing is aimed at identifying the reference spectral si...
research
∙
05/07/2015
Fast Spectral Unmixing based on Dykstra's Alternating Projection
This paper presents a fast spectral unmixing algorithm based on Dykstra'...
research
∙
04/22/2015
Combining local regularity estimation and total variation optimization for scale-free texture segmentation
Texture segmentation constitutes a standard image processing task, cruci...
research
∙
04/17/2015
Hyperspectral pansharpening: a review
Pansharpening aims at fusing a panchromatic image with a multispectral o...
research
∙
02/10/2015
Fast Fusion of Multi-Band Images Based on Solving a Sylvester Equation
This paper proposes a fast multi-band image fusion algorithm, which comb...
research
∙
10/17/2014
Bayesian estimation of the multifractality parameter for image texture using a Whittle approximation
Texture characterization is a central element in many image processing a...
research
∙
09/19/2014
Hyperspectral and Multispectral Image Fusion based on a Sparse Representation
This paper presents a variational based approach to fusing hyperspectral...
research
∙
01/22/2014
Nonlinear hyperspectral unmixing with robust nonnegative matrix factorization
This paper introduces a robust mixing model to describe hyperspectral da...
research
∙
10/01/2013
Joint Bayesian estimation of close subspaces from noisy measurements
In this letter, we consider two sets of observations defined as subspace...
research
∙
07/23/2013
Bayesian Fusion of Multi-Band Images
In this paper, a Bayesian fusion technique for remotely sensed multi-ban...
research
∙
04/06/2013
Nonlinear unmixing of hyperspectral images: models and algorithms
When considering the problem of unmixing hyperspectral images, most of t...
research
∙
03/15/2013
Variational Semi-blind Sparse Deconvolution with Orthogonal Kernel Bases and its Application to MRFM
We present a variational Bayesian method of joint image reconstruction a...
research
∙
07/23/2012
Nonlinear spectral unmixing of hyperspectral images using Gaussian processes
This paper presents an unsupervised algorithm for nonlinear unmixing of ...
research
∙
03/21/2012
Semi-blind Sparse Image Reconstruction with Application to MRFM
We propose a solution to the image deconvolution problem where the convo...
research
∙
02/28/2012
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches
Imaging spectrometers measure electromagnetic energy scattered in their ...
research
∙
01/18/2011