Beyond Pretty Pictures: Combined Single- and Multi-Image Super-Resolution for Sentinel-2 Images
Aditya Retnanto,
Son Le,
Sebastian Mueller,
Armin Leitner,
Michael Riffler,
Konrad Schindler and
Yohan Iddawela
Additional contact information
Aditya Retnanto: Asian Development Bank
Son Le: Asian Development Bank
Sebastian Mueller: Asian Development Bank
Armin Leitner: GeoVille Information Systems and Data Processing GmbH
Michael Riffler: GeoVille Information Systems and Data Processing GmbH
Konrad Schindler: Institute of Geodesy and Photogrammetry at ETH Zürich
Yohan Iddawela: Asian Development Bank
No 823, ADB Economics Working Paper Series from Asian Development Bank
Abstract:
Super-resolution (SR) aims to increase the resolution of satellite images by reconstructing high-frequency details, which go beyond naive upsampling. This has particular relevance for Earth observation missions like Sentinel-2, which offer frequent, regular coverage at no cost, but at coarse resolution. The pixel footprint of Sentinel-2 coverage is too large to capture small features like houses, streets, or hedge rows. To address this, we present SEN4X, a hybrid super-resolution architecture that combines the advantages of single image and multi-image techniques. It combines temporal oversampling from repeated Sentinel-2 acquisitions with a learned prior from high-resolution Pléiades Neo data. In doing so, SEN4X upgrades Sentinel-2 imagery to 2.5 m ground sampling distance. We test the super-resolved images on urban land-cover classification in Ha Noi, Viet Nam. We find that they lead to significant performance improvement over state-of-the-art super resolution baselines.
Keywords: super-resolution; remote sensing; Sentinel-2; land-cover classification (search for similar items in EconPapers)
JEL-codes: Y8 (search for similar items in EconPapers)
Pages: 31
Date: 2025-11-26
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Persistent link: https://EconPapers.repec.org/RePEc:ris:adbewp:021790
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