The official PyTorch implementation of FIDNet.
The primary implementation of the FIDNet can be found in the following directory:
model/FIDNet.py
For training and testing, you can use the code provided in the RAS2S.
Simply place the model file model/FIDNet.py into the basic/models/competing_methods directory, and ensure that the path to checkpoint/fidnet.pth is correctly set.
If any parts of our paper and code help your research, please consider citing us and giving a star to our repository.
@inproceedings{xiao2024bridging,
title={Bridging Fourier and Spatial-Spectral Domains for Hyperspectral Image Denoising},
author={Xiao, Jiahua and Liu, Yang and Zhang, Shizhou and Wei, Xing},
booktitle={Proceedings of the 32nd ACM International Conference on Multimedia},
year={2024}
}
@inproceedings{xiao2024region,
title={Region-Aware Sequence-to-Sequence Learning for Hyperspectral Denoising},
author={Xiao, Jiahua and Liu, Yang and Wei, Xing},
booktitle={European Conference on Computer Vision},
year={2024}
}