Model Inspired Autoencoder for Unsupervised Hyperspectral Image Super-Resolution

This article focuses on hyperspectral image (HSI) super-resolution that aims to fuse a low-spatial-resolution HSI and a high-spatial-resolution multispectral image to form a high-spatial-resolution HSI (HR-HSI). Existing deep learning-based approaches are mostly supervised that rely on a large numbe...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2022, Vol.60, p.1-12
Hauptverfasser:	Liu, Jianjun, Wu, Zebin, Xiao, Liang, Wu, Xiao-Jun
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Autoencoder Coders Decoding Deep learning Energy resolution Fuses hyperspectral image (HSI) Hyperspectral imaging Image resolution Machine learning nonnegative matrix factorization (NMF) Point spread functions Resolution Response functions Spatial resolution Spectral sensitivity super-resolution Superresolution Tensors unfolding
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