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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.01868 |
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| _version_ | 1866911542449012736 |
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| author | Audisio, Pierre Belletti, Barbara Pustelnik, Nelly |
| author_facet | Audisio, Pierre Belletti, Barbara Pustelnik, Nelly |
| contents | The temporal and spatial analysis of river dynamics is a key factor for studying and understanding human impacts on floodplains. To assess the changes taking place, it is necessary to have high-resolution images with a large spatial coverage and a high temporal revisit frequency over the long term. Satellite imagery meets several of these criteria. For instance, Sentinel data provide high-resolution images but only after 2015. Therefore, to study water surface evolution prior to this date, it is necessary to rely on other satellite images such as Landsat, which offers longer historical coverage, albeit with lower spatial resolution. In this study, we aim to increase the spatial resolution of Landsat data from 30 to 10 meters (resolution of Sentinel images). To achieve this goal, we develop an innovative single image super-resolution method based on a plug-and-play approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_01868 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Plug-and-play forward backward algorithm to restore Landsat images: A preliminary step to uncover the history of surface waters Audisio, Pierre Belletti, Barbara Pustelnik, Nelly Signal Processing The temporal and spatial analysis of river dynamics is a key factor for studying and understanding human impacts on floodplains. To assess the changes taking place, it is necessary to have high-resolution images with a large spatial coverage and a high temporal revisit frequency over the long term. Satellite imagery meets several of these criteria. For instance, Sentinel data provide high-resolution images but only after 2015. Therefore, to study water surface evolution prior to this date, it is necessary to rely on other satellite images such as Landsat, which offers longer historical coverage, albeit with lower spatial resolution. In this study, we aim to increase the spatial resolution of Landsat data from 30 to 10 meters (resolution of Sentinel images). To achieve this goal, we develop an innovative single image super-resolution method based on a plug-and-play approach. |
| title | Plug-and-play forward backward algorithm to restore Landsat images: A preliminary step to uncover the history of surface waters |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2603.01868 |