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Dokumenttyp:
Zeitschriftenaufsatz 
Autor(en):
Liebel, Lukas; Körner, Marco 
Titel:
Single-Image Super Resolution for Multispectral Remote Sensing Data Using Convolutional Neural Networks 
Abstract:
In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can bene...    »
 
Stichworte:
Computer Vision, Superresolution, without_full_paper_review 
Zeitschriftentitel:
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS) 
Jahr:
2016 
Band / Volume:
XLI-B3 
Seitenangaben Beitrag:
883--890 
Sprache:
en