Deep Plug-and-Play Prior for Hyperspectral Image Restoration (Neurocomputing 2022)
Zeqiang Lai, Kaixuan Wei, Ying Fu
- 2021-01-22: Add a command line client for testing single image or list of images in folders.
- 2021-01-21: Release demo code for each task.
- Install the requirments
# Pytorch >= 1.8
conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
conda install -c conda-forge opencv
pip install -r requirements.txt
- Clone the repo
git clone https://github.com/Zeqiang-Lai/DPHSIR.git
cd DPHSIR
pip install -e .
- Run cli or playgrounds
- Download the sample input if you don't have one.
- Download the pretrained model,
grunet.pth
, put it inplaygrounds/grunet.pth
.
# run cli
python cli/main.py -i [input_path] [task]
# run playground
python playgrounds/deblur.py
If you find our work useful for your research, please consider citing our paper :)
@article{lai2022dphsir,
title = {Deep plug-and-play prior for hyperspectral image restoration},
journal = {Neurocomputing},
volume = {481},
pages = {281-293},
year = {2022},
issn = {0925-2312},
doi = {https://doi.org/10.1016/j.neucom.2022.01.057},
author = {Zeqiang Lai and Kaixuan Wei and Ying Fu},
}