Asymmetric Dual-Direction Quasi-Recursive Network for Single Hyperspectral Image Super-Resolution

Author:

Wang Heng1ORCID,Wang Cong2ORCID,Yuan Yuan2ORCID

Affiliation:

1. School of Computer Science and the School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China

2. School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China

Funder

National Key Research and Development Program of China

National Science Fund for Distinguished Young Scholars

National Natural Science Foundation of China

China National Postdoctoral Program for Innovative Talents

Fellowship of China Postdoctoral Science Foundation

Basic and Applied Basic Research Foundation of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Cited by 6 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. Multi-dimensional attention-aided transposed ConvBiLSTM network for hyperspectral image super-resolution;Computer Vision and Image Understanding;2024-11

2. Neighbor Spectra Maintenance and Context Affinity Enhancement for Single Hyperspectral Image Super-Resolution;IEEE Transactions on Geoscience and Remote Sensing;2024

3. Statistical Texture Awareness Network for Hyperspectral Image Classification;IEEE Transactions on Geoscience and Remote Sensing;2024

4. Language-Guided Progressive Attention for Visual Grounding in Remote Sensing Images;IEEE Transactions on Geoscience and Remote Sensing;2024

5. HS-McHF: Hypersharpening With Multicomponent-Based Hierarchical Features Fusion Network;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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