A Band Divide-and-Conquer Multispectral and Hyperspectral Image Fusion Method

The nonoverlapped spectrum range between low spatial resolution (LR) hyperspectral (HS) and high spatial resolution (HR) multispectral (MS) images has been a fundamental but challenging problem for MS/HS fusion. The spectrum of HS data is generally 400-2500 nm, and the spectrum of MS data is general...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2022, Vol.60, p.1-13
Hauptverfasser:	Sun, Weiwei, Ren, Kai, Meng, Xiangchao, Xiao, Chenchao, Yang, Gang, Peng, Jiangtao
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Band spectra Bayes methods Computational efficiency Computer applications Computer vision Computing time Datasets Deep learning Divide-and-conquer framework (BDCF) Gaofen-5 (GF-5) hyperspectral (HS) Hyperspectral imaging Image fusion Image processing Methods multispectral (MS) neural network framework Neural networks Resolution Signal resolution Spatial discrimination Spatial resolution Spectral bands Spectral sensitivity Sun
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