A deep spatial/spectral descriptor of hyperspectral texture using scattering transform

Abstract : A technique to describe the spatial / spectral features of hyperspectral images is introduced. These descriptors aim at representing the content of the image while considering invariances related to the texture and to its geometric transformations, so called spatial invariances. Moreover, we also consider spectral invariances which are related to the composition of the pixels. Our approach is based on the scattering transform, which provides an useful framework for deep learning classification. The goal through these descriptors is to improve pixel-wise classification of hyperspectral images.
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Communication dans un congrès
2016 IEEE International Conference on Image Processing (ICIP), Sep 2016, Phoenix, United States. 2016, 〈10.1109/ICIP.2016.7533024〉
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https://hal-mines-paristech.archives-ouvertes.fr/hal-01446966
Contributeur : Jesus Angulo <>
Soumis le : jeudi 26 janvier 2017 - 14:51:35
Dernière modification le : vendredi 27 octobre 2017 - 17:36:02

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Gianni Franchi, Jesus Angulo. A deep spatial/spectral descriptor of hyperspectral texture using scattering transform. 2016 IEEE International Conference on Image Processing (ICIP), Sep 2016, Phoenix, United States. 2016, 〈10.1109/ICIP.2016.7533024〉. 〈hal-01446966〉

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