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

• 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, 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
• Language: English
• Published: HAL CCSD 2020
• Subjects: 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]; Totten Glacier; Antarc*; Antarctica
• Online Access: https://hal.archives-ouvertes.fr/hal-03103824; https://hal.archives-ouvertes.fr/hal-03103824/document; https://hal.archives-ouvertes.fr/hal-03103824/file/DTIS20138.1610034556_preprint.pdf; https://doi.org/10.1109/RadarConf2043947.2020.9266643

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.