Haze transfer and feature aggregation network for real-world single image dehazing

This package contains the source code which is associated with the following paper:

Huafeng Li, Jirui Gao, Yafei Zhang, Minghong Xie, Zhengtao Yu, “Haze transfer and feature aggregation network for real-world single image dehazing.”

Edited by Jirui Gao

Usage of this code is free for research purposes only.

Thank you.

Requirements:

CUDA  10.0
Python  3.7.7
Pytorch  1.5.0
torchvision  0.6.0
numpy  1.17.4

Get Started

1.Install:

download the code
git clone https://github.com/lhf12278/HTFA-Net.git
cd HTFA-Net

2.Datasets

Download the synthetic hazy datasets that were generated by ourselves through the links below: HTset:Baidu Pan（password：36sv）

3.If you dont want to download the synthetic hazy datasets, you can also generate by yourself. Put your Real Images into '''test_data/RealHaze_image''' and put Clear Images into '''test_data\Clear_image''':

cd HTFA-Net/Generating_HazeImages
python test.py

4.Dehazing:

Dehazing the hazy images that were generated by ourselves.

    cd HTFA-Net/dehaze
    python test.py

Dehazing the real hazy images: Replace the '''dehaze/checkpoint/dehaze_best_model.pth''' file with the '''dehaze_best_model.pth''' file in '''dehaze/checkpoint/real/'''.

    cd HTFA-Net/dehaze
    python test.py

Contact:

Don't hesitate to contact me if you meet any problems when using this code.

Jirui Gao
Faculty of Information Engineering and Automation
Kunming University of Science and Technology                                                           
Email: 2945266153@qq.com

Acknowledgements

Our code is based on https://proteus1991.github.io/GridDehazeNet,https://github.com/zhilin007/FFA-Net and https://github.com/HUSTSYJ/DA_dahazing.