@inproceedings{c83fb7b21ff3429ea6a2d95aa44eac00,
title = "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.",
keywords = "Computer vision, Deep learning, Hyperspectral images, Pixel-wise classification, Wavelet transform",
author = "Gianni Franchi and Jesus Angulo",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 23rd IEEE International Conference on Image Processing, ICIP 2016 ; Conference date: 25-09-2016 Through 28-09-2016",
year = "2016",
month = aug,
day = "3",
doi = "10.1109/ICIP.2016.7533024",
language = "English",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",
pages = "3568--3572",
booktitle = "2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings",
}