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Beyond Pretty Pictures: Combined Single- and Multi-Image Super-Resolution for Sentinel-2 Images

Author

Listed:
  • 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)

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.

Suggested Citation

  • Aditya Retnanto & Son Le & Sebastian Mueller & Armin Leitner & Michael Riffler & Konrad Schindler & Yohan Iddawela, 2025. "Beyond Pretty Pictures: Combined Single- and Multi-Image Super-Resolution for Sentinel-2 Images," ADB Economics Working Paper Series 823, Asian Development Bank.
    • Handle: RePEc:ris:adbewp:021790
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    JEL classification:

    • Y8 - Miscellaneous Categories - - Related Disciplines

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