Journal of The Remote Sensing Society of Japan
Online ISSN : 1883-1184
Print ISSN : 0289-7911
ISSN-L : 0289-7911
Special Section for Application of Remote Sensing Data in The Open Data Era : Case Study
Deep-Learning-Based Super Resolution for Satellite Imagery
Issei KAWASHIMARyosuke NAKAMURA
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2018 Volume 38 Issue 2 Pages 131-136

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Abstract

This paper presents a super resolution (SR) method for satellite imagery based on deep learning. From this preliminary study, we found that the performance of SR strongly depends on the variety of the training data set. A new strategy that combines SR and selection is proposed to improve the accuracy and flexibility of the method.

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© 2018 The Remote Sensing Society of Japan
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