The angular kernel in machine learning for hyperspectral data classification
International audience Support vector machines have been investigated with success for hyperspectral data classification. In this paper, we propose a new kernel to measure spectral similarity, called the angular kernel. We provide some of its properties, such as its invariance to illumination energy...
Published in: | 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing |
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ftunivnantes:oai:HAL:hal-01966042v1 2023-05-15T16:50:13+02:00 The angular kernel in machine learning for hyperspectral data classification Honeine, Paul Richard, Cédric Laboratoire Modélisation et Sûreté des Systèmes (LM2S) Institut Charles Delaunay (ICD) Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS) Laboratoire Hippolyte Fizeau (FIZEAU) Université Nice Sophia Antipolis (1965 - 2019) (UNS) COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS) Reykjavik, Iceland 2010 https://hal.archives-ouvertes.fr/hal-01966042 https://hal.archives-ouvertes.fr/hal-01966042/document https://hal.archives-ouvertes.fr/hal-01966042/file/10.angular.pdf https://doi.org/10.1109/WHISPERS.2010.5594908 en eng HAL CCSD info:eu-repo/semantics/altIdentifier/doi/10.1109/WHISPERS.2010.5594908 hal-01966042 https://hal.archives-ouvertes.fr/hal-01966042 https://hal.archives-ouvertes.fr/hal-01966042/document https://hal.archives-ouvertes.fr/hal-01966042/file/10.angular.pdf doi:10.1109/WHISPERS.2010.5594908 info:eu-repo/semantics/OpenAccess Proc. IEEE Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS) https://hal.archives-ouvertes.fr/hal-01966042 Proc. IEEE Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS), 2010, Reykjavik, Iceland. pp.1-4, ⟨10.1109/WHISPERS.2010.5594908⟩ data handling Gaussian processes geophysical image processing image classification learning (artificial intelligence) angular kernel hyperspectral data classification illumination energy Gaussian kernel urban classification task hyperspectral images Kernel Support vector machines Hyperspectral imaging Machine learning Spatial resolution Hyperspectral data spectral angle SVM reproducing kernel [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] info:eu-repo/semantics/conferenceObject Conference papers 2010 ftunivnantes https://doi.org/10.1109/WHISPERS.2010.5594908 2022-09-07T00:10:57Z International audience Support vector machines have been investigated with success for hyperspectral data classification. In this paper, we propose a new kernel to measure spectral similarity, called the angular kernel. We provide some of its properties, such as its invariance to illumination energy, as well as connection to previous work. Furthermore, we show that the performance of a classifier associated to the angular kernel is comparable to the Gaussian kernel, in the sense of universality. We derive a class of kernels based on the angular kernel, and study the performance on an urban classification task. Conference Object Iceland Université de Nantes: HAL-UNIV-NANTES 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing 1 4 |
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Université de Nantes: HAL-UNIV-NANTES |
op_collection_id |
ftunivnantes |
language |
English |
topic |
data handling Gaussian processes geophysical image processing image classification learning (artificial intelligence) angular kernel hyperspectral data classification illumination energy Gaussian kernel urban classification task hyperspectral images Kernel Support vector machines Hyperspectral imaging Machine learning Spatial resolution Hyperspectral data spectral angle SVM reproducing kernel [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] |
spellingShingle |
data handling Gaussian processes geophysical image processing image classification learning (artificial intelligence) angular kernel hyperspectral data classification illumination energy Gaussian kernel urban classification task hyperspectral images Kernel Support vector machines Hyperspectral imaging Machine learning Spatial resolution Hyperspectral data spectral angle SVM reproducing kernel [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] Honeine, Paul Richard, Cédric The angular kernel in machine learning for hyperspectral data classification |
topic_facet |
data handling Gaussian processes geophysical image processing image classification learning (artificial intelligence) angular kernel hyperspectral data classification illumination energy Gaussian kernel urban classification task hyperspectral images Kernel Support vector machines Hyperspectral imaging Machine learning Spatial resolution Hyperspectral data spectral angle SVM reproducing kernel [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] |
description |
International audience Support vector machines have been investigated with success for hyperspectral data classification. In this paper, we propose a new kernel to measure spectral similarity, called the angular kernel. We provide some of its properties, such as its invariance to illumination energy, as well as connection to previous work. Furthermore, we show that the performance of a classifier associated to the angular kernel is comparable to the Gaussian kernel, in the sense of universality. We derive a class of kernels based on the angular kernel, and study the performance on an urban classification task. |
author2 |
Laboratoire Modélisation et Sûreté des Systèmes (LM2S) Institut Charles Delaunay (ICD) Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS) Laboratoire Hippolyte Fizeau (FIZEAU) Université Nice Sophia Antipolis (1965 - 2019) (UNS) COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS) |
format |
Conference Object |
author |
Honeine, Paul Richard, Cédric |
author_facet |
Honeine, Paul Richard, Cédric |
author_sort |
Honeine, Paul |
title |
The angular kernel in machine learning for hyperspectral data classification |
title_short |
The angular kernel in machine learning for hyperspectral data classification |
title_full |
The angular kernel in machine learning for hyperspectral data classification |
title_fullStr |
The angular kernel in machine learning for hyperspectral data classification |
title_full_unstemmed |
The angular kernel in machine learning for hyperspectral data classification |
title_sort |
angular kernel in machine learning for hyperspectral data classification |
publisher |
HAL CCSD |
publishDate |
2010 |
url |
https://hal.archives-ouvertes.fr/hal-01966042 https://hal.archives-ouvertes.fr/hal-01966042/document https://hal.archives-ouvertes.fr/hal-01966042/file/10.angular.pdf https://doi.org/10.1109/WHISPERS.2010.5594908 |
op_coverage |
Reykjavik, Iceland |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
Proc. IEEE Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS) https://hal.archives-ouvertes.fr/hal-01966042 Proc. IEEE Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS), 2010, Reykjavik, Iceland. pp.1-4, ⟨10.1109/WHISPERS.2010.5594908⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1109/WHISPERS.2010.5594908 hal-01966042 https://hal.archives-ouvertes.fr/hal-01966042 https://hal.archives-ouvertes.fr/hal-01966042/document https://hal.archives-ouvertes.fr/hal-01966042/file/10.angular.pdf doi:10.1109/WHISPERS.2010.5594908 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1109/WHISPERS.2010.5594908 |
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2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing |
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