DRT

Dynamic Range Transformer (DRT): Learning Enhanced Log-Perceptual Information with Swin-Fourier Convolution Network for HDR Imaging

Heunseung Lim, Joongchol Shin, Jinsol Choi, and Joonki Paik. In IEEE Conference on Image Processing (ICIP), 2023 [Paper]

Requirements

• Python 3.8
• PyTorch 1.9.1
• MATLAB (for data preparation)

Usage

Data preparation

1. Download data from [dataset]
2. Create data using the Matlab executable located in './GeneralH5Data/PrepareData.m'. AHDR) *(GenerH5data folders from AHDR)

Testing

1. Install this repository and the required packages. A pretrained model is in ./trained-model.
2. Prepare dataset.
   1. Download from [dataset]
   2. Import and test the image based on the file in the test-flow.txt file.
   3. Create and test a testing file using the file in the AHDR) Github link './GeneralH5Data/PrepareData.m'
3. Run python script_testing.py files.

Training

1. Prepare dataset.

2. Download dataset.
3. Similar to testing, create training-only data and learn using the 'script_training.py' file. Hyperparameters must be adjusted.

Pre-trained model download (.pkl)

https://drive.google.com/file/d/1mdMtj4ZbpeMEohyABlTbhwUG40u1hEyN/view?usp=drive_link

Citation

If you use this code for your research, please cite our paper.

@INPROCEEDINGS{10223189,
  author={Lim, Heunseung and Shin, Joongchol and Choi, Jinsol and Paik, Joonki},
  booktitle={2023 IEEE International Conference on Image Processing (ICIP)}, 
  title={Dynamic Range Transformer (DRT): Learning Enhanced Log-Perceptual Information with Swin-Fourier Convolution Network for HDR Imaging}, 
  year={2023},
  volume={},
  number={},
  pages={3040-3044},
  keywords={Training;Image sensors;Image color analysis;Convolution;Neural networks;Lighting;Dynamic range;high dynamic range;transformer;log-Euclidean metric},
  doi={10.1109/ICIP49359.2023.10223189}}


@article{yan2021dual,
  title={Dual-attention-guided network for ghost-free high dynamic range imaging},
  author={Yan, Qingsen and Gong, Dong and Shi, Javen Qinfeng and van den Hengel, Anton and Shen, Chunhua and Reid, Ian and Zhang, Yanning},
  journal={International Journal of Computer Vision},
  pages={1--19},
  year={2021},
  publisher={Springer}
}
@article{yan2019attention,
  title={Attention-guided Network for Ghost-free High Dynamic Range Imaging},
  author={Yan, Qingsen and Gong, Dong and Shi, Qinfeng and Hengel, Anton van den and Shen, Chunhua and Reid, Ian and Zhang, Yanning},
  journal={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019}
  pages={1751-1760}
}

Code

Code modified from [AHDR] https://github.com/qingsenyangit/AHDRNet, thanks to Qingsen Yan.