Improvement of pixel classification by the ...
Document type :
Article dans une revue scientifique: Article original
Permalink :
Title :
Improvement of pixel classification by the simultaneous use of spectral and spatial information in the framework of spectroscopic imaging
Author(s) :
Nardecchia, Alessandro [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Vitale, Raffaele [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Ziemons, Eric [Auteur]
Université de Liège
Centre International de Rencontres Mathématiques [CIRM]
Duponchel, Ludovic [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]
Vitale, Raffaele [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Ziemons, Eric [Auteur]
Université de Liège
Centre International de Rencontres Mathématiques [CIRM]
Duponchel, Ludovic [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Journal title :
Analytica Chimica Acta
Volume number :
1242
Publication date :
2023
English keyword(s) :
Hyperspectral imaging
classification
Partial least squares discriminant analysis (PLS-DA)
spectral and spatial information fusion
2D stationary wavelet transform (2D- SWT)
classification
Partial least squares discriminant analysis (PLS-DA)
spectral and spatial information fusion
2D stationary wavelet transform (2D- SWT)
HAL domain(s) :
Sciences du Vivant [q-bio]
English abstract : [en]
Hyperspectral imaging technology is developing in a very fast way. We find it today in many analytical developments using different spectroscopies for sample classification purposes. Instrumental developments allow us to ...
Show more >Hyperspectral imaging technology is developing in a very fast way. We find it today in many analytical developments using different spectroscopies for sample classification purposes. Instrumental developments allow us to acquire more and more data in shorter and shorter periods of time while improving their quality. Therefore, we are going in the right direction as far as the measure is concerned. On the other hand, we can make a more mixed assessment for the hyperspectral imaging data processing. Indeed, the data acquired in spectroscopic imaging have the particularity of encoding both spectral and spatial information. Unfortunately, in chemometrics, almost all classification approaches today only use spectral information from three-dimensional hyperspectral data arrays. To be more precise, an approach encompassing the unfolding/refolding of such arrays is often applied beforehand because the majority of algorithms for analysing these data are not capable of handling them in their original structure. Spatial information is therefore lost during the chemometric exploration. The study of the spectral part of the acquired data array alone is clearly a limitation that we propose to overcome in this work. 2-D Stationary Wavelet Transform will be used in the data preprocessing phase to ensure the joint use of spectral and spatial information. Two spectroscopic datasets will then be used to evaluate the potential of our approach in the context of supervised classification.Show less >
Show more >Hyperspectral imaging technology is developing in a very fast way. We find it today in many analytical developments using different spectroscopies for sample classification purposes. Instrumental developments allow us to acquire more and more data in shorter and shorter periods of time while improving their quality. Therefore, we are going in the right direction as far as the measure is concerned. On the other hand, we can make a more mixed assessment for the hyperspectral imaging data processing. Indeed, the data acquired in spectroscopic imaging have the particularity of encoding both spectral and spatial information. Unfortunately, in chemometrics, almost all classification approaches today only use spectral information from three-dimensional hyperspectral data arrays. To be more precise, an approach encompassing the unfolding/refolding of such arrays is often applied beforehand because the majority of algorithms for analysing these data are not capable of handling them in their original structure. Spatial information is therefore lost during the chemometric exploration. The study of the spectral part of the acquired data array alone is clearly a limitation that we propose to overcome in this work. 2-D Stationary Wavelet Transform will be used in the data preprocessing phase to ensure the joint use of spectral and spatial information. Two spectroscopic datasets will then be used to evaluate the potential of our approach in the context of supervised classification.Show less >
Audience :
Non spécifiée
Popular science :
Non
Administrative institution(s) :
ENSCL
CNRS
Université de Lille
CNRS
Université de Lille
Collections :
Research team(s) :
Propriétés magnéto structurales des matériaux (PMSM)
Submission date :
2024-02-21T17:11:59Z
2024-02-26T14:15:54Z
2024-02-26T14:15:54Z