no code implementations • 7 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.
no code implementations • 12 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.
3 code implementations • 12 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.
no code implementations • 11 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.
1 code implementation • 3 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.
no code implementations • 3 Sep 2015 • Filipe Condessa, José Bioucas-Dias, Carlos Castro, John Ozolek, Jelena Kovačević
We introduce a new supervised algorithm for image classification with rejection using multiscale contextual information.
no code implementations • 7 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.
no code implementations • 14 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.
no code implementations • 19 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.
no code implementations • 31 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.