GLF-CR: SAR-Enhanced Cloud Removal with Global-Local Fusion

This repository contains the codes for the paper "GLF-CR: SAR-Enhanced Cloud Removal with Global-Local Fusion"

If you use the codes for your research, please cite us accordingly:

@article{xu2022glf,
  title={GLF-CR: SAR-enhanced cloud removal with global--local fusion},
  author={Xu, Fang and Shi, Yilei and Ebel, Patrick and Yu, Lei and Xia, Gui-Song and Yang, Wen and Zhu, Xiao Xiang},
  journal={ISPRS Journal of Photogrammetry and Remote Sensing},
  volume={192},
  pages={268--278},
  year={2022},
  publisher={Elsevier}
}

Prerequisites & Installation

This code has been tested with CUDA 10.1 and Python 3.6.

conda create -n GLF-CR python=3.6
pip install torch==1.4.0 torchvision==0.5.0
pip install scipy
pip install rasterio
pip install timm==0.3.2

cd ./codes/FAC/kernelconv2d/
python setup.py clean
python setup.py install --user

Get Started

You can download the pretrained model from here and put it in './cpkg'.

Use the following command to test the neural network:

python test_CR.py

Credits

This code is based on the codes available in the STFAN repo, slow-motion and SwinIR. I am grateful to the authors for making the original source code available.

Contact

We are glad to hear if you have any suggestions and questions.

Please send email to xufang@whu.edu.cn