Sentinel-2A Image Fusion Using a Machine Learning Approach

The multispectral instrument (MSI) carried by Sentinel-2A has 13 spectral bands with various spatial resolutions (i.e., four 10-m, six 20-m, and three 60-m bands). A wide range of applications requires a 10-m resolution for all spectral bands, including the 20- and 60-m bands. To achieve this requir...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2019-12, Vol.57 (12), p.9589-9601
Hauptverfasser:	Wang, Jing, Huang, Bo, Zhang, Hankui K., Ma, Peifeng
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Band spectra Computer simulation Computer vision Distortion Earth Image degradation Image fusion Image processing Learning algorithms Machine learning Modulation transfer function Optical communication Regression models Resolution Response functions Sentinel-2A sharpening Spatial resolution Spectral bands Spectral sensitivity Support vector machines support vector regression (SVR) Transforms Visual aspects
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