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Optimal Transport for Data Fusion in Remote Sensing

Nicolas Courty 1 Rémi Flamary 2 Devis Tuia 3 Thomas Corpetti 4
1 OBELIX - Environment observation with complex imagery
UBS - Université de Bretagne Sud, IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
4 FLUMINANCE - Fluid Flow Analysis, Description and Control from Image Sequences
CEMAGREF - Centre national du machinisme agricole, du génie rural, des eaux et forêts, Inria Rennes – Bretagne Atlantique
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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https://hal.archives-ouvertes.fr/hal-01377234
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Submitted on : Thursday, October 6, 2016 - 3:28:54 PM
Last modification on : Thursday, April 2, 2020 - 1:54:59 AM
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  • HAL Id : hal-01377234, version 1

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

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