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High resolution remote sensing imagery is used in broad range of tasks,including detection and classification of objects. High-resolution imagery ishowever expensive, while lower resolution imagery is often freely available andcan be used by the public for range of social good applications. To that end,we curate a multi-spectral multi-image super-resolution dataset, usingPlanetScope imagery from the SpaceNet 7 challenge as the high resolutionreference and multiple Sentinel-2 revisits of the same imagery as thelow-resolution imagery. We present the first results of applying multi-imagesuper-resolution (MISR) to multi-spectral remote sensing imagery. We,additionally, introduce a radiometric consistency module into MISR model the topreserve the high radiometric resolution of the Sentinel-2 sensor. We show thatMISR is superior to single-image super-resolution and other baselines on arange of image fidelity metrics. Furthermore, we conduct the first assessmentof the utility of multi-image super-resolution on building delineation, showingthat utilising multiple images results in better performance in thesedownstream tasks.

Multi-Spectral Multi-Image Super-Resolution of Sentinel-2 with Radiometric Consistency Losses and Its Effect on Building Delineation