Co-clustering for hyperspectral images.
Type de document :
Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès sans actes
URL permanente :
Titre :
Co-clustering for hyperspectral images.
Auteur(s) :
Jacques, Julien [Auteur]
Ruckebusch, Cyril [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Ruckebusch, Cyril [Auteur]

Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Titre de la manifestation scientifique :
6th International Conference in Spectral Imaging
Ville :
Chamonix
Pays :
France
Date de début de la manifestation scientifique :
2016-07
Discipline(s) HAL :
Informatique [cs]/Traitement des images [eess.IV]
Résumé en anglais : [en]
Clustering is often used for hyperspectral images in order to assign sets of pixels into a number of different homogeneous groups called clusters. As a result, pixels in the same cluster have similar spectra, i.e. are close ...
Lire la suite >Clustering is often used for hyperspectral images in order to assign sets of pixels into a number of different homogeneous groups called clusters. As a result, pixels in the same cluster have similar spectra, i.e. are close to each other in a certain sense. Clustering is a core technique of the chemometrics toolbox but some limitations can be pointed for hyperspectral imaging. A first limitation of clustering is that it only considers information in the spectral dimension. Another is that it groups whole vectors. This means that if one or a few elements of the vectors differ significantly, the vectors cannot be clustered together. These limitations may result in suboptimal grouping.Lire moins >
Lire la suite >Clustering is often used for hyperspectral images in order to assign sets of pixels into a number of different homogeneous groups called clusters. As a result, pixels in the same cluster have similar spectra, i.e. are close to each other in a certain sense. Clustering is a core technique of the chemometrics toolbox but some limitations can be pointed for hyperspectral imaging. A first limitation of clustering is that it only considers information in the spectral dimension. Another is that it groups whole vectors. This means that if one or a few elements of the vectors differ significantly, the vectors cannot be clustered together. These limitations may result in suboptimal grouping.Lire moins >
Langue :
Anglais
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
CNRS
ENSCL
Université de Lille
ENSCL
Université de Lille
Date de dépôt :
2020-06-08T14:11:03Z
2020-06-09T07:18:56Z
2020-06-09T07:18:56Z
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