Interactive Autoencoders With Degradation Constraint For Hyperspectral Super-Resolution
Author:
Affiliation:
1. Aerospace Information Research Institute, Chinese Academy of Sciences,Key Laboratory of Computational Optical Imaging Technology,Beijing,China
2. College of Geography and Environment, Liaocheng University,Liaocheng,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10281394/10281399/10282922.pdf?arnumber=10282922
Reference10 articles.
1. MHF-Net: An Interpretable Deep Network for Multispectral and Hyperspectral Image Fusion
2. Coupled Convolutional Neural Network With Adaptive Response Function Learning for Unsupervised Hyperspectral Super Resolution
3. Hyperspectral Super-Resolution by Coupled Spectral Unmixing
4. Deep learning in multimodal remote sensing data fusion: A comprehensive review
5. Fusing Hyperspectral and Multispectral Images via Coupled Sparse Tensor Factorization
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Model-Informed Multistage Unsupervised Network for Hyperspectral Image Super-Resolution;IEEE Transactions on Geoscience and Remote Sensing;2024
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