Search Results for author: José Bioucas-Dias

Found 10 papers, 2 papers with code

Matrix Cofactorization for Joint Representation Learning and Supervised Classification -- Application to Hyperspectral Image Analysis

no code implementations7 Feb 2019 Adrien Lagrange, Mathieu Fauvel, Stéphane May, José Bioucas-Dias, Nicolas Dobigeon

The attribution vectors of the clustering are then used as features vectors for the classification task, i. e., the coding vectors of the corresponding factorization problem.

Classification Clustering +3

An Extension of Averaged-Operator-Based Algorithms

no code implementations12 Jun 2018 Miguel Simões, José Bioucas-Dias, Luis B. Almeida

Many of the algorithms used to solve minimization problems with sparsity-inducing regularizers are generic in the sense that they do not take into account the sparsity of the solution in any particular way.

Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural network

3 code implementations12 Mar 2018 Charis Lanaras, José Bioucas-Dias, Silvano Galliani, Emmanuel Baltsavias, Konrad Schindler

The aim of this research is to super-resolve the lower-resolution (20 m and 60 m Ground Sampling Distance - GSD) bands to 10 m GSD, so as to obtain a complete data cube at the maximal sensor resolution.


Restoring STM images via Sparse Coding: noise and artifact removal

no code implementations11 Oct 2016 João P. Oliveira, Ana Bragança, José Bioucas-Dias, Mário Figueiredo, Luís Alcácer, Jorge Morgado, Quirina Ferreira

In this article, we present a denoising algorithm to improve the interpretation and quality of scanning tunneling microscopy (STM) images.

Denoising regression

A Framework for Fast Image Deconvolution with Incomplete Observations

1 code implementation3 Feb 2016 Miguel Simões, Luis B. Almeida, José Bioucas-Dias, Jocelyn Chanussot

In this paper, we propose a new deconvolution framework for images with incomplete observations that allows us to work with diagonalized convolution operators, and therefore is very fast.

Demosaicking Image Deconvolution

Semiblind Hyperspectral Unmixing in the Presence of Spectral Library Mismatches

no code implementations7 Jul 2015 Xiao Fu, Wing-Kin Ma, José Bioucas-Dias, Tsung-Han Chan

The dictionary-aided sparse regression (SR) approach has recently emerged as a promising alternative to hyperspectral unmixing (HU) in remote sensing.

Hyperspectral Unmixing regression

A convex formulation for hyperspectral image superresolution via subspace-based regularization

no code implementations14 Nov 2014 Miguel Simões, José Bioucas-Dias, Luis B. Almeida, Jocelyn Chanussot

Hyperspectral remote sensing images (HSIs) usually have high spectral resolution and low spatial resolution.

Hyperspectral and Multispectral Image Fusion based on a Sparse Representation

no code implementations19 Sep 2014 Qi Wei, José Bioucas-Dias, Nicolas Dobigeon, Jean-Yves Tourneret

This paper presents a variational based approach to fusing hyperspectral and multispectral images.

Hyperspectral image superresolution: An edge-preserving convex formulation

no code implementations31 Mar 2014 Miguel Simões, José Bioucas-Dias, Luis B. Almeida, Jocelyn Chanussot

Hyperspectral remote sensing images (HSIs) are characterized by having a low spatial resolution and a high spectral resolution, whereas multispectral images (MSIs) are characterized by low spectral and high spatial resolutions.

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