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...
Published in: | 2020 IEEE Radar Conference (RadarConf20) |
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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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ftonera:oai:HAL:hal-03103824v1 2024-09-15T17:42:28+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) 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 ftonera https://doi.org/10.1109/RadarConf2043947.2020.9266643 2024-07-29T23:39:41Z 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 ONERA: HAL (French Aerospace Lab) 2020 IEEE Radar Conference (RadarConf20) 1 6 |
institution |
Open Polar |
collection |
ONERA: HAL (French Aerospace Lab) |
op_collection_id |
ftonera |
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) 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 |
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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1810489046092218368 |