Automatic Estimation of Ice Bottom Surfaces from Radar Imagery
Ground-penetrating radar on planes and satellites now makes it practical to collect 3D observations of the subsurface structure of the polar ice sheets, providing crucial data for understanding and tracking global climate change. But converting these noisy readings into useful observations is genera...
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ftdatacite:10.48550/arxiv.1712.07758 2023-05-15T14:28:50+02:00 Automatic Estimation of Ice Bottom Surfaces from Radar Imagery Xu, Mingze Crandall, David J Fox, Geoffrey C Paden, John D 2017 https://dx.doi.org/10.48550/arxiv.1712.07758 https://arxiv.org/abs/1712.07758 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Computer Vision and Pattern Recognition cs.CV FOS Computer and information sciences Preprint Article article CreativeWork 2017 ftdatacite https://doi.org/10.48550/arxiv.1712.07758 2022-04-01T10:01:03Z Ground-penetrating radar on planes and satellites now makes it practical to collect 3D observations of the subsurface structure of the polar ice sheets, providing crucial data for understanding and tracking global climate change. But converting these noisy readings into useful observations is generally done by hand, which is impractical at a continental scale. In this paper, we propose a computer vision-based technique for extracting 3D ice-bottom surfaces by viewing the task as an inference problem on a probabilistic graphical model. We first generate a seed surface subject to a set of constraints, and then incorporate additional sources of evidence to refine it via discrete energy minimization. We evaluate the performance of the tracking algorithm on 7 topographic sequences (each with over 3000 radar images) collected from the Canadian Arctic Archipelago with respect to human-labeled ground truth. : 5 pages, 3 figures, published in ICIP 2017 Report Arctic Archipelago Arctic Canadian Arctic Archipelago Climate change DataCite Metadata Store (German National Library of Science and Technology) Arctic Canadian Arctic Archipelago |
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DataCite Metadata Store (German National Library of Science and Technology) |
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ftdatacite |
language |
unknown |
topic |
Computer Vision and Pattern Recognition cs.CV FOS Computer and information sciences |
spellingShingle |
Computer Vision and Pattern Recognition cs.CV FOS Computer and information sciences Xu, Mingze Crandall, David J Fox, Geoffrey C Paden, John D Automatic Estimation of Ice Bottom Surfaces from Radar Imagery |
topic_facet |
Computer Vision and Pattern Recognition cs.CV FOS Computer and information sciences |
description |
Ground-penetrating radar on planes and satellites now makes it practical to collect 3D observations of the subsurface structure of the polar ice sheets, providing crucial data for understanding and tracking global climate change. But converting these noisy readings into useful observations is generally done by hand, which is impractical at a continental scale. In this paper, we propose a computer vision-based technique for extracting 3D ice-bottom surfaces by viewing the task as an inference problem on a probabilistic graphical model. We first generate a seed surface subject to a set of constraints, and then incorporate additional sources of evidence to refine it via discrete energy minimization. We evaluate the performance of the tracking algorithm on 7 topographic sequences (each with over 3000 radar images) collected from the Canadian Arctic Archipelago with respect to human-labeled ground truth. : 5 pages, 3 figures, published in ICIP 2017 |
format |
Report |
author |
Xu, Mingze Crandall, David J Fox, Geoffrey C Paden, John D |
author_facet |
Xu, Mingze Crandall, David J Fox, Geoffrey C Paden, John D |
author_sort |
Xu, Mingze |
title |
Automatic Estimation of Ice Bottom Surfaces from Radar Imagery |
title_short |
Automatic Estimation of Ice Bottom Surfaces from Radar Imagery |
title_full |
Automatic Estimation of Ice Bottom Surfaces from Radar Imagery |
title_fullStr |
Automatic Estimation of Ice Bottom Surfaces from Radar Imagery |
title_full_unstemmed |
Automatic Estimation of Ice Bottom Surfaces from Radar Imagery |
title_sort |
automatic estimation of ice bottom surfaces from radar imagery |
publisher |
arXiv |
publishDate |
2017 |
url |
https://dx.doi.org/10.48550/arxiv.1712.07758 https://arxiv.org/abs/1712.07758 |
geographic |
Arctic Canadian Arctic Archipelago |
geographic_facet |
Arctic Canadian Arctic Archipelago |
genre |
Arctic Archipelago Arctic Canadian Arctic Archipelago Climate change |
genre_facet |
Arctic Archipelago Arctic Canadian Arctic Archipelago Climate change |
op_rights |
arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
op_doi |
https://doi.org/10.48550/arxiv.1712.07758 |
_version_ |
1766302977515061248 |