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

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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.

Andrea Bordone Molini, Diego Valsesia, Giulia Fracastoro, Enrico Magli• 2020

Related benchmarks

TaskDatasetResultRank
Multi-image Super-resolutionProba-V (val)
NIR PSNR (dB)47.93
10
Multitemporal Super-ResolutionProba-V NIR (val)
cPSNR47.93
10
Multitemporal Super-ResolutionProba-V RED (val)
cPSNR50.08
10
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