Methods for evaluating the resolution of 3D data derived from satellite images
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arXiv
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| Auteurs principaux: | , , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866911005255139328 |
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| author | Selby, Christina Bindl, Holden Feldman, Tyler Skow, Andrew Acosta, Nicolas Norena Hagstrom, Shea Brown, Myron |
| author_facet | Selby, Christina Bindl, Holden Feldman, Tyler Skow, Andrew Acosta, Nicolas Norena Hagstrom, Shea Brown, Myron |
| contents | 3D data derived from satellite images is essential for scene modeling applications requiring large-scale coverage or involving locations not accessible by airborne lidar or cameras. Measuring the resolution of this data is important for determining mission utility and tracking improvements. In this work, we consider methods to evaluate the resolution of point clouds, digital surface models, and 3D mesh models. We describe 3D metric evaluation tools and workflows that enable automated evaluation based on high-resolution reference airborne lidar, and we present results of analyses with data of varying quality. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_11876 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Methods for evaluating the resolution of 3D data derived from satellite images Selby, Christina Bindl, Holden Feldman, Tyler Skow, Andrew Acosta, Nicolas Norena Hagstrom, Shea Brown, Myron Computer Vision and Pattern Recognition Image and Video Processing 3D data derived from satellite images is essential for scene modeling applications requiring large-scale coverage or involving locations not accessible by airborne lidar or cameras. Measuring the resolution of this data is important for determining mission utility and tracking improvements. In this work, we consider methods to evaluate the resolution of point clouds, digital surface models, and 3D mesh models. We describe 3D metric evaluation tools and workflows that enable automated evaluation based on high-resolution reference airborne lidar, and we present results of analyses with data of varying quality. |
| title | Methods for evaluating the resolution of 3D data derived from satellite images |
| topic | Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2506.11876 |