MCR-ALS of hyperspectral images with ...
Document type :
Article dans une revue scientifique: Article original
Permalink :
Title :
MCR-ALS of hyperspectral images with spatio-spectral fuzzy clustering constraint
Author(s) :
Firmani, Patrizia [Auteur]
Hugelier, Siewert [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Marini, Federico [Auteur]
Ruckebusch, Cyril [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Hugelier, Siewert [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Marini, Federico [Auteur]
Ruckebusch, Cyril [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Journal title :
Chemometrics and Intelligent Laboratory Systems
Volume number :
179
Pages :
85-91
Publication date :
2018-08
HAL domain(s) :
Chimie/Chimie théorique et/ou physique
Chimie/Chimie théorique et/ou physique
Chimie/Chimie théorique et/ou physique
English abstract : [en]
In recent years, in the context of the application of Multivariate Curve Resolution (MCR) to hyperspectral image analysis, attention has been more and more put onto the possibility of exploiting not only the spectral but ...
Show more >In recent years, in the context of the application of Multivariate Curve Resolution (MCR) to hyperspectral image analysis, attention has been more and more put onto the possibility of exploiting not only the spectral but also the spatial information for constraining the algorithmic solution. Examples involve the introduction of different spatial constraints during the iterative Alternating Least Squares (ALS) calculation of the MCR solution or the post-processing of the score images using conventional image processing techniques. In this framework, this work proposes an approach for constraining concentration distribution maps within MCR-ALS analysis of hyperspectral images, based on the use of spatio-spectral fuzzy clustering in order to obtain smoother, more contrasted, and better interpretable chemical images. We show the relevance of the proposed approach and investigate the effect of the application of a spectral-spatial fuzzy clustering constraint on samples of different nature.Show less >
Show more >In recent years, in the context of the application of Multivariate Curve Resolution (MCR) to hyperspectral image analysis, attention has been more and more put onto the possibility of exploiting not only the spectral but also the spatial information for constraining the algorithmic solution. Examples involve the introduction of different spatial constraints during the iterative Alternating Least Squares (ALS) calculation of the MCR solution or the post-processing of the score images using conventional image processing techniques. In this framework, this work proposes an approach for constraining concentration distribution maps within MCR-ALS analysis of hyperspectral images, based on the use of spatio-spectral fuzzy clustering in order to obtain smoother, more contrasted, and better interpretable chemical images. We show the relevance of the proposed approach and investigate the effect of the application of a spectral-spatial fuzzy clustering constraint on samples of different nature.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
CNRS
ENSCL
Université de Lille
ENSCL
Université de Lille
Collections :
Submission date :
2021-11-16T08:23:32Z
2024-02-23T09:08:09Z
2024-02-23T09:08:09Z