Learning-based superresolution land cover mapping

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Learning-based superresolution land cover mapping

Super-resolution mapping (SRM) is a technique for generating a fine spatial resolution land cover map from coarse spatial resolution fraction images estimated by soft classification. The prior model used to describe the fine spatial resolution land cover pattern is a key issue in SRM. Here, a novel...

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Bibliographic Details
Main Authors:	Ling, Feng, Zhang, Yihang, Foody, Giles M., Li, Xiaodong, Zhang, Xiuhua, Fang, Shiming, Li, Wenbo, Du, Yun
Format:	Article
Published:	Institute of Electrical and Electronics Engineers 2016
Subjects:	Super-resolution mapping; learning database; patch pairs; neighboring patches
Online Access:	https://eprints.nottingham.ac.uk/32958/

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