Transmission and Color-guided Network for Underwater Image Enhancement (ICME 2023)(Paper)

The Pytorch Implementation of ''Transmission and Color-guided Network for Underwater Image Enhancement''.

Introduction

In this project, we use Ubuntu 20.04.1, Python 3.8, Pytorch 1.11.0 and one NVIDIA RTX A6000 GPU.

Running

Testing

Download the pretrained model pretrained model.

Check the model and image pathes in test.py, and then run:

python test.py

Training

To train the model, you need to prepare our dataset.

Check the dataset path in train.py, and then run:

python train.py

Citation

If you find ATDCnet is useful in your research, please cite our paper:

@article{mu2023transmission,
  title={Transmission and Color-guided Network for Underwater Image Enhancement},
  author={Mu, Pan and Fang, Jing and Qian, Haotian and Bai, Cong},
  journal={arXiv preprint arXiv:2308.04892},
  year={2023}
}