Analysis of dense coregistration methods applied to optical and SAR time-series for ice flow estimations

International audience This article considers the application of two dense coregistration algorithms to the estimation of ice flow. These algorithms estimate displacements at each pixel of the image and can be applied to pairs of radar, optical and radar/optical images. This flexibility combined with...

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Published in:2020 IEEE Radar Conference (RadarConf20)
Main Authors: Charrier, Laurane, Godet, Pierre, Rambour, Clément, Weissgerber, Flora, Erdmann, Simon, Koeniguer, Elise Colin
Other Authors: DTIS, ONERA, Université Paris Saclay Palaiseau, ONERA-Université Paris-Saclay, Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance (LISTIC), Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry ), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers CNAM (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), DEMR, ONERA, Université Paris Saclay Palaiseau, DOTA, ONERA, Université Paris Saclay Palaiseau
Format: Conference Object
Language:English
Published: HAL CCSD 2020
Subjects:
Online Access:https://hal.science/hal-03103824
https://hal.science/hal-03103824/document
https://hal.science/hal-03103824/file/DTIS20138.1610034556_preprint.pdf
https://doi.org/10.1109/RadarConf2043947.2020.9266643
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spelling ftconservatoiren:oai:HAL:hal-03103824v1 2024-05-12T07:56:37+00:00 Analysis of dense coregistration methods applied to optical and SAR time-series for ice flow estimations Charrier, Laurane Godet, Pierre Rambour, Clément Weissgerber, Flora Erdmann, Simon Koeniguer, Elise Colin DTIS, ONERA, Université Paris Saclay Palaiseau ONERA-Université Paris-Saclay Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance (LISTIC) Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry ) Centre d'études et de recherche en informatique et communications (CEDRIC) Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers CNAM (CNAM) HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM) DEMR, ONERA, Université Paris Saclay Palaiseau DOTA, ONERA, Université Paris Saclay Palaiseau Florence, Italy 2020-09-21 https://hal.science/hal-03103824 https://hal.science/hal-03103824/document https://hal.science/hal-03103824/file/DTIS20138.1610034556_preprint.pdf https://doi.org/10.1109/RadarConf2043947.2020.9266643 en eng HAL CCSD IEEE info:eu-repo/semantics/altIdentifier/doi/10.1109/RadarConf2043947.2020.9266643 ISBN: 978-1-7281-8942-0 hal-03103824 https://hal.science/hal-03103824 https://hal.science/hal-03103824/document https://hal.science/hal-03103824/file/DTIS20138.1610034556_preprint.pdf doi:10.1109/RadarConf2043947.2020.9266643 info:eu-repo/semantics/OpenAccess 2020 IEEE Radar Conference (RadarConf20) https://hal.science/hal-03103824 2020 IEEE Radar Conference (RadarConf20), Sep 2020, Florence, Italy. pp.1-6, ⟨10.1109/RadarConf2043947.2020.9266643⟩ SAR images optical images coregistration optical flow deep learning dense multi-modal ice flow glaciers [INFO]Computer Science [cs] [PHYS]Physics [physics] [SPI]Engineering Sciences [physics] info:eu-repo/semantics/conferenceObject Conference papers 2020 ftconservatoiren https://doi.org/10.1109/RadarConf2043947.2020.9266643 2024-04-12T01:40:53Z International audience This article considers the application of two dense coregistration algorithms to the estimation of ice flow. These algorithms estimate displacements at each pixel of the image and can be applied to pairs of radar, optical and radar/optical images. This flexibility combined with the dense estimation should improve both spatial and temporal resolutions of glacier displacement maps. Several tests are carried out on Sentinel-1 and Sentinel-2 images on Totten glacier in Antarctica. We assess the reliability of the considered algorithms by applying them to real and emulated pairs of images based on displacement fields previously estimated in the literature. Conference Object Antarc* Antarctica Totten Glacier Archives ouvertes du Conservatoire national des arts et métiers Totten Glacier ENVELOPE(116.333,116.333,-66.833,-66.833) 2020 IEEE Radar Conference (RadarConf20) 1 6
institution Open Polar
collection Archives ouvertes du Conservatoire national des arts et métiers
op_collection_id ftconservatoiren
language English
topic SAR images
optical images
coregistration
optical flow
deep learning
dense
multi-modal
ice flow
glaciers
[INFO]Computer Science [cs]
[PHYS]Physics [physics]
[SPI]Engineering Sciences [physics]
spellingShingle SAR images
optical images
coregistration
optical flow
deep learning
dense
multi-modal
ice flow
glaciers
[INFO]Computer Science [cs]
[PHYS]Physics [physics]
[SPI]Engineering Sciences [physics]
Charrier, Laurane
Godet, Pierre
Rambour, Clément
Weissgerber, Flora
Erdmann, Simon
Koeniguer, Elise Colin
Analysis of dense coregistration methods applied to optical and SAR time-series for ice flow estimations
topic_facet SAR images
optical images
coregistration
optical flow
deep learning
dense
multi-modal
ice flow
glaciers
[INFO]Computer Science [cs]
[PHYS]Physics [physics]
[SPI]Engineering Sciences [physics]
description International audience This article considers the application of two dense coregistration algorithms to the estimation of ice flow. These algorithms estimate displacements at each pixel of the image and can be applied to pairs of radar, optical and radar/optical images. This flexibility combined with the dense estimation should improve both spatial and temporal resolutions of glacier displacement maps. Several tests are carried out on Sentinel-1 and Sentinel-2 images on Totten glacier in Antarctica. We assess the reliability of the considered algorithms by applying them to real and emulated pairs of images based on displacement fields previously estimated in the literature.
author2 DTIS, ONERA, Université Paris Saclay Palaiseau
ONERA-Université Paris-Saclay
Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance (LISTIC)
Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )
Centre d'études et de recherche en informatique et communications (CEDRIC)
Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers CNAM (CNAM)
HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)
DEMR, ONERA, Université Paris Saclay Palaiseau
DOTA, ONERA, Université Paris Saclay Palaiseau
format Conference Object
author Charrier, Laurane
Godet, Pierre
Rambour, Clément
Weissgerber, Flora
Erdmann, Simon
Koeniguer, Elise Colin
author_facet Charrier, Laurane
Godet, Pierre
Rambour, Clément
Weissgerber, Flora
Erdmann, Simon
Koeniguer, Elise Colin
author_sort Charrier, Laurane
title Analysis of dense coregistration methods applied to optical and SAR time-series for ice flow estimations
title_short Analysis of dense coregistration methods applied to optical and SAR time-series for ice flow estimations
title_full Analysis of dense coregistration methods applied to optical and SAR time-series for ice flow estimations
title_fullStr Analysis of dense coregistration methods applied to optical and SAR time-series for ice flow estimations
title_full_unstemmed Analysis of dense coregistration methods applied to optical and SAR time-series for ice flow estimations
title_sort analysis of dense coregistration methods applied to optical and sar time-series for ice flow estimations
publisher HAL CCSD
publishDate 2020
url https://hal.science/hal-03103824
https://hal.science/hal-03103824/document
https://hal.science/hal-03103824/file/DTIS20138.1610034556_preprint.pdf
https://doi.org/10.1109/RadarConf2043947.2020.9266643
op_coverage Florence, Italy
long_lat ENVELOPE(116.333,116.333,-66.833,-66.833)
geographic Totten Glacier
geographic_facet Totten Glacier
genre Antarc*
Antarctica
Totten Glacier
genre_facet Antarc*
Antarctica
Totten Glacier
op_source 2020 IEEE Radar Conference (RadarConf20)
https://hal.science/hal-03103824
2020 IEEE Radar Conference (RadarConf20), Sep 2020, Florence, Italy. pp.1-6, ⟨10.1109/RadarConf2043947.2020.9266643⟩
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1109/RadarConf2043947.2020.9266643
ISBN: 978-1-7281-8942-0
hal-03103824
https://hal.science/hal-03103824
https://hal.science/hal-03103824/document
https://hal.science/hal-03103824/file/DTIS20138.1610034556_preprint.pdf
doi:10.1109/RadarConf2043947.2020.9266643
op_rights info:eu-repo/semantics/OpenAccess
op_doi https://doi.org/10.1109/RadarConf2043947.2020.9266643
container_title 2020 IEEE Radar Conference (RadarConf20)
container_start_page 1
op_container_end_page 6
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