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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Main Authors: | , , , , , |
Other Authors: | , , , , , , , |
Format: | Conference Object |
Language: | English |
Published: |
HAL CCSD
2020
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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 |
Summary: | 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. |
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