Hyperspectral Image Super-Resolution Using Deep Feature Matrix Factorization

Hyperspectral images (HSIs) can describe the subtle differences in the spectral signatures of materials. However, they have low spatial resolution due to various hardware limitations. Improving it via postprocess without an auxiliary high-resolution (HR) image still remains a challenging problem. In...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2019-08, Vol.57 (8), p.6055-6067
Hauptverfasser:	Xie, Weiying, Jia, Xiuping, Li, Yunsong, Lei, Jie
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Band selection Correlation Correlation analysis deep neural network (DNN) Factorization Feature extraction hyperspectral image (HSI) Hyperspectral imaging Image reconstruction Image resolution Mathematical analysis matrix factorization Matrix methods Neural networks Prototypes Reflectance Remote sensing Resolution Spatial resolution Spectra Spectral signatures super-resolution (SR) Vectors
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