DeepSUM++: Non-local Deep Neural Network for Super-Resolution of Unregistered Multitemporal Images

Deep learning methods for super-resolution of a remote sensing scene from multiple unregistered low-resolution images have recently gained attention thanks to a challenge proposed by the European Space Agency. This paper presents an evolution of the winner of the challenge, showing how incorporating...

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Hauptverfasser: Molini, Andrea Bordone, Valsesia, Diego, Fracastoro, Giulia, Magli, Enrico
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Sprache:eng
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Zusammenfassung:Deep learning methods for super-resolution of a remote sensing scene from multiple unregistered low-resolution images have recently gained attention thanks to a challenge proposed by the European Space Agency. This paper presents an evolution of the winner of the challenge, showing how incorporating non-local information in a convolutional neural network allows to exploit self-similar patterns that provide enhanced regularization of the super-resolution problem. Experiments on the dataset of the challenge show improved performance over the state-of-the-art, which does not exploit non-local information.
DOI:10.48550/arxiv.2001.06342