Code of the paper "Image Dehazing by Joint Estimation of Transmittance and Airlight using Bi-Directional Consistency Loss Minimized FCN"
Input | Dehzed |
---|---|
- For Running
- Python 2
- keras
- scipy
- numpy
- scikit-image
- matplotlib
$ cd src/
$ python main.py <hazy_image_dir> <output_dir>
This runs the code in the supplied images.
$python main.py ../data/hazy_img/ ../data/out/
├── data
│ ├── hazy_img
│ │ └── lawn1_input.png
│ └── out
│ ├── ADelhi_Smog-PTI.jpg
│ ├── Delhi_Smog-PTI.jpg
│ └── TDelhi_Smog-PTI.jpg
├── models
│ └── model_weights.h5 # Trained model
├── Readme.md
└── src
├── gf.py # guided filter
├── main_file.py
├── main.py # main file
└── model.py # model
Ranjan Mondal, Sanchayan Santra and Bhabatosh Chanda. "Image Dehazing by Joint Estimation of Transmittance and Airlight using Bi-Directional Consistency Loss Minimized FCN" Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop. 2018, pp-920-928.
BibTeX:
@inproceedings{mondal2018image,
title={Image Dehazing by Joint Estimation of Transmittance and Airlight using Bi-Directional Consistency Loss Minimized FCN},
author={Mondal, Ranjan and Santra, Sanchayan and Chanda, Bhabatosh},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops},
pages={920--928},
year={2018}
}