Optimal Transport for Data Fusion in Remote Sensing

Abstract : One of the main objective of data fusion is the integration of several acquisition of the same physical object, in order to build a new consistent representation that embeds all the information from the different modalities. In this paper, we propose the use of optimal transport theory as a powerful mean of establishing correspondences between the modalities. After reviewing important properties and computational aspects, we showcase its application to three remote sensing fusion problems: domain adaptation, time series averaging and change detection in LIDAR data.
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Communication dans un congrès
IGARSS, Jul 2016, Beijing, China. 2016
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Contributeur : Nicolas Courty <>
Soumis le : jeudi 6 octobre 2016 - 15:28:54
Dernière modification le : mercredi 12 juillet 2017 - 01:14:11
Document(s) archivé(s) le : vendredi 3 février 2017 - 16:22:04


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  • HAL Id : hal-01377234, version 1


Nicolas Courty, Rémi Flamary, Devis Tuia, Thomas Corpetti. Optimal Transport for Data Fusion in Remote Sensing. IGARSS, Jul 2016, Beijing, China. 2016. <hal-01377234>



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