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On The Role of Alias and Band-Shift for Sentinel-2 Super-Resolution (2302.11494v2)
Published 22 Feb 2023 in cs.CV and eess.IV
Abstract: In this work, we study the problem of single-image super-resolution (SISR) of Sentinel-2 imagery. We show that thanks to its unique sensor specification, namely the inter-band shift and alias, that deep-learning methods are able to recover fine details. By training a model using a simple $L_1$ loss, results are free of hallucinated details. For this study, we build a dataset of pairs of images Sentinel-2/PlanetScope to train and evaluate our super-resolution (SR) model.