GuidedNet

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# GuidedNet
Code for the paper: "GuidedNet: A General CNN Fusion Framework via Highresolution Guidance for Hyperspectral Image Super-resolution", TCYB, 2023.

![image](https://user-images.githubusercontent.com/49515620/219292206-67afadb0-c6f9-4790-9841-0e8c00337f86.png)
![image](https://user-images.githubusercontent.com/49515620/219292234-7c312b73-ed95-42cc-bcfb-bf1a7d03a7de.png)

# Plateform.

Python 3.8

Tensorflow 1.15.2

TensorLayer 1.8.0rc

# Demo
main_train.py for training code, and

test.py for testing code

The traning data are too big, they are not provided. You can follow the simulation method in the paper and generate the .mat file for training

# Test Data
Test data include，

Cave: https://pan.baidu.com/s/1Grc3K0dp9N8oFfqUDPYTGQ?pwd=7833 code：7833

Harvard: https://pan.baidu.com/s/18tGPamlNz20cPPq3TvyyAw?pwd=4rly  code：4rly

# Bib Reference
@ARTICLE{10035506,
  author={Ran, Ran and Deng, Liang-Jian and Jiang, Tai-Xiang and Hu, Jin-Fan and Chanussot, Jocelyn and Vivone, Gemine},
  journal={IEEE Transactions on Cybernetics},
  title={GuidedNet: A General CNN Fusion Framework via High-Resolution Guidance for Hyperspectral Image Super-Resolution},
  year={2023},
  volume={},
  number={},
  pages={1-14},
  doi={10.1109/TCYB.2023.3238200}}

GuidedNet

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