Unsupervised and Unregistered Hyperspectral Image Super-Resolution With Mutual Dirichlet-Net

Hyperspectral images (HSIs) provide rich spectral information that has contributed to the successful performance improvement of numerous computer vision and remote sensing tasks. However, it can only be achieved at the expense of images' spatial resolution. HSI super-resolution (HSI-SR), thus,...

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Vydané v:	IEEE transactions on geoscience and remote sensing Ročník 60; s. 1 - 18
Hlavní autori:	Qu, Ying, Qi, Hairong, Kwan, Chiman, Yokoya, Naoto, Chanussot, Jocelyn
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.01.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Predmet:	Accuracy Bayes methods Coders Computer Science Computer vision Data mining Dimensions Dirichlet problem Hyperspectral image (HSI) Hyperspectral imaging Image reconstruction Image resolution Information processing mutual information (MI) Optimization Registration Remote sensing Representations Resolution Sensors Signal and Image Processing Spatial data Spatial discrimination Spatial resolution Spectra super-resolution (SR) Superresolution Tensors unregistered unsupervised deep learning mutual information (MI) Hyperspectral image (HSI) unregistered super-resolution (SR) unsupervised deep learning
ISSN:	0196-2892, 1558-0644
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