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Optimal transport for data fusion in remote sensing


Courty, Nicolas; Flamary, Rémi; Tuia, Devis; Corpetti, Thomas (2016). Optimal transport for data fusion in remote sensing. In: IGARSS 2016 (IEEE International Geoscience and Remote Sensing Symposium), Beijing, 10 July 2016 - 15 July 2016, 3571-3574.

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.

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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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Event End Date:15 July 2016
Deposited On:14 Feb 2017 13:46
Last Modified:31 Aug 2017 18:14
Publisher:Institute of Electrical and Electronics Engineers
Series Name:IEEE International Geoscience and Remote Sensing Symposium Proceedings
ISSN:2153-6996
ISBN:978-1-5090-3332-4
Additional Information:© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher DOI:https://doi.org/10.1109/IGARSS.2016.7729925

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