MCR-ALS of hyperspectral images with ...
Type de document :
Article dans une revue scientifique: Article original
URL permanente :
Titre :
MCR-ALS of hyperspectral images with spatio-spectral fuzzy clustering constraint
Auteur(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
Titre de la revue :
Chemometrics and Intelligent Laboratory Systems
Numéro :
179
Pagination :
85-91
Date de publication :
2018-08
Discipline(s) HAL :
Chimie/Chimie théorique et/ou physique
Chimie/Chimie théorique et/ou physique
Chimie/Chimie théorique et/ou physique
Résumé en anglais : [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 ...
Lire la suite >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.Lire moins >
Lire la suite >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.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
CNRS
ENSCL
Université de Lille
ENSCL
Université de Lille
Collections :
Date de dépôt :
2021-11-16T08:23:32Z
2024-02-23T09:08:09Z
2024-02-23T09:08:09Z