Optimal transport for data fusion in remote sensing

Nicolas Courty, Remi Flamary, Devis Tuia, Thomas Corpetti

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3571-3574
Number of pages4
ISBN (Electronic)9781509033324
ISBN (Print)9781509033331
DOIs
Publication statusPublished - Nov 2016
Externally publishedYes
Event36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China
Duration: 10 Jul 201615 Jul 2016

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2016-November

Conference

Conference36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
CountryChina
CityBeijing
Period10/07/1615/07/16

Keywords

  • change detection
  • domain adaptation
  • LIDAR
  • Optimal transport
  • time series analysis

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  • Cite this

    Courty, N., Flamary, R., Tuia, D., & Corpetti, T. (2016). Optimal transport for data fusion in remote sensing. In 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings (pp. 3571-3574). [7729925] (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2016-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2016.7729925