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Super-resolution of Sensinel-2 imagery using generative adversarial networks

Author
Salgueiro, L.; Marcello, J.; Vilaplana, V.
Type of activity
Journal article
Journal
Remote sensing
Date of publication
2020-07-28
Volume
12
Number
15
First page
2424:1
Last page
2424:25
DOI
10.3390/rs12152424
Project funding
Multimodal Signal Processing and Machine Learning on Graphs
Repository
http://hdl.handle.net/2117/329988 Open in new window
URL
https://www.mdpi.com/2072-4292/12/15/2424 Open in new window
Abstract
Sentinel-2 satellites provide multi-spectral optical remote sensing images with four bands at 10 m of spatial resolution. These images, due to the open data distribution policy, are becoming an important resource for several applications. However, for small scale studies, the spatial detail of these images might not be sufficient. On the other hand, WorldView commercial satellites offer multi-spectral images with a very high spatial resolution, typically less than 2 m, but their use can be impra...
Citation
Salgueiro, L.; Marcello, J.; Vilaplana, V. Super-resolution of Sensinel-2 imagery using generative adversarial networks. "Remote sensing", 28 Juliol 2020, vol. 12, núm. 15, p. 2424:1-2424:25.
Keywords
Deep learning, Generative adversarial network, Sentinel-2, Super-resolution, WorldView
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

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