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arXiv 2001.06342eess.IVcs.CVcs.LG

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

Politecnico di Torino(都灵理工大学)

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

英文摘要:

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.

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