Implicit Neural Representation Learning for Hyperspectral Image Super-Resolution

Author:

Zhang Kaiwei1ORCID,Zhu Dandan2ORCID,Min Xiongkuo1ORCID,Zhai Guangtao1ORCID

Affiliation:

1. Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai, China

2. Institute of AI Education, East China Normal University, Shanghai, China

Funder

National Natural Science Foundation of China

Foundation of Key Laboratory of Artificial Intelligence, Ministry of Education, China

National Key Research and Development Program of China

Shanghai Municipal Science and Technology Major Project

Shanghai Pujiang Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

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1. Hyperspectral Image Joint Super-Resolution via Local Implicit Spatial-Spectral Function Learning;IEEE Photonics Journal;2024-06

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3. Implicit Neural Representation-Based Hybrid Digital-Analog Image Delivery;2024 International Conference on Computing, Networking and Communications (ICNC);2024-02-19

4. A continuous digital elevation representation model for DEM super-resolution;ISPRS Journal of Photogrammetry and Remote Sensing;2024-02

5. Hyperspectral Image Super-Resolution With ConvLSTM Skip-Connections;IEEE Transactions on Geoscience and Remote Sensing;2024

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