MuS2: A Benchmark for Sentinel-2 Multi-Image Super-Resolution

Abstract

Insufficient spatial resolution of satellite imagery, including Sentinel-2 data, is a serious limitation in many practical use cases. To mitigate this problem, super-resolution reconstruction is receiving considerable attention from the remote sensing community. When it is performed from multiple images captured at subsequent revisits, it may benefit from information fusion, leading to enhanced reconstruction accuracy. One of the obstacles in multi-image super-resolution consists in the scarcity of real-life benchmark datasets-most of the research was performed for simulated data which do not fully reflect the operating conditions. In this letter, we introduce a new MuS2 benchmark for multi-image super-resolution reconstruction of Sentinel-2 images, with WorldView-2 imagery used as the highresolution reference. Within MuS2, we publish the first end-toend evaluation procedure for this problem which we expect to help the researchers in advancing the state of the art in multiimage super-resolution for Sentinel-2 imagery.