@inproceedings{73ac0ff07eee47748ffd869f7a088b60,
title = "Supervised planetary unmixing with optimal transport",
abstract = "This paper is focused on spectral unmixing and present an original technique based on Optimal Transport. Optimal Transport consists in estimating a plan that transports a spectrum onto another with minimal cost, enabling to compute an associated distance (Wasserstein distance) that can be used as an alternative metric to compare hyperspectral data. This is exploited for spectral unmixing where abundances in each pixel are estimated on the basis of their projections in a Wasserstein sense (Bregman projections) onto known endmembers. In this work an over-complete dictionary is used to deal with internal variability between endmembers, while a regularization term, also based on Wasserstein distance, is used to promote prior proportion knowledge in the endmember groups. Experiments are performed on real hyperspectral data of asteroid 4-Vesta.",
keywords = "Bregman Projection, Endmember Variability, Optimal Transport, Spectral Unmixing, Wassertein Distance",
author = "Sina Nakhostin and Nicolas Courty and Remi Flamary and Thomas Corpetti",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2016 ; Conference date: 21-08-2016 Through 24-08-2016",
year = "2016",
month = jun,
day = "28",
doi = "10.1109/WHISPERS.2016.8071694",
language = "English",
series = "Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing",
publisher = "IEEE Computer Society",
booktitle = "2016 8th Workshop on Hyperspectral Image and Signal Processing",
}