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Deep WaveNet

Wavelength-based Attributed Deep Neural Network for Underwater Image Restoration

accepted in ACM Transactions on Multimedia Computing, Communications, and Applications
Prasen Kumar Sharma, Ira Bisht, and Arijit Sur.
Web-app has been released (basic version). Best viewed in Firefox latest version. Note that Heroku allows CPU-based computations only with limited memory. Hence, the app processes input image with a lower-resolution of 256x256. Use the above codes only to reproduce the original results.

Google Colab demo: Open In Colab

Block

arXiv version

Contents

  1. Results
  2. Prerequisites
  3. Datasets Preparation
  4. Usage
  5. Evaluation Metrics
  6. Processing underwater degraded videos
  7. For Underwater Semantic Segmentation and 2D pose Estimation Results
  8. License and Citations
  9. Send us feedback
  10. Acknowledgement
  11. Future Releases

Results

Block

Prerequisites

Build TypeLinuxMacOSWindows
ScriptenvTBA[TBA]

Also, the codes work with minimum requirements as given below.

# tested with the following dependencies on Ubuntu 16.04 LTS system:
Python 3.5.2
Pytorch '1.0.1.post2'
torchvision 0.2.2
opencv 4.0.0
scipy 1.2.1
numpy 1.16.2
tqdm

To install using linux env

pip install -r requirements.txt

Datasets Preparation

To test the Deep WaveNet on EUVP dataset
cd uie_euvp
---testing_dir_inp
---testing_dir_gt
To test the Deep WaveNet on UIEB and Challenging-60 datasets
cd uie_uieb
---testing_dir_inp
---testing_dir_gt
To test the Deep WaveNet on UFO-120 dataset
cd super-resolution
cd 2X
---testing_dir_inp
---testing_dir_gt
For training

Usage

For testing
export CUDA_VISIBLE_DEVICES=0 #[optional]
python test.py  
For training
export CUDA_VISIBLE_DEVICES=0 #[optional]
python train.py --checkpoints_dir --batch_size --learning_rate             

Evaluation Metrics

  ### compute SSIM and PSNR
  SSIM_measures, PSNR_measures = SSIMs_PSNRs(CLEAN_DIR, result_dir)
  print("SSIM on {0} samples".format(len(SSIM_measures))+"\n")
  print("Mean: {0} std: {1}".format(np.mean(SSIM_measures), np.std(SSIM_measures))+"\n")
  print("PSNR on {0} samples".format(len(PSNR_measures))+"\n")
  print("Mean: {0} std: {1}".format(np.mean(PSNR_measures), np.std(PSNR_measures))+"\n")
  measure_UIQMs(result_dir)
MethodMSEPSNRSSIM
Deep WaveNet.2928.62.83
MethodMSEPSNRSSIM
Deep WaveNet.6021.57.80
MethodPSNRSSIMUIQM
Deep WaveNet (2X)25.71.772.99
Deep WaveNet (3X)25.23.762.96
Deep WaveNet (4X)25.08.742.97

Processing underwater degraded videos

cd uw_video_processing
python test.py

For Underwater Semantic Segmentation and 2D pose Estimation Results

License and Citation

@misc{sharma2021wavelengthbased,
      title={Wavelength-based Attributed Deep Neural Network for Underwater Image Restoration}, 
      author={Prasen Kumar Sharma and Ira Bisht and Arijit Sur},
      year={2021},
      eprint={2106.07910},
      archivePrefix={arXiv},
      primaryClass={eess.IV}
}

 @article{islam2019fast,
     title={Fast Underwater Image Enhancement for Improved Visual Perception},
     author={Islam, Md Jahidul and Xia, Youya and Sattar, Junaed},
     journal={IEEE Robotics and Automation Letters (RA-L)},
     volume={5},
     number={2},
     pages={3227--3234},
     year={2020},
     publisher={IEEE}
}

@ARTICLE{8917818,  
    author={Li, Chongyi 
            and Guo, Chunle 
            and Ren, Wenqi 
            and Cong, Runmin 
            and Hou, Junhui 
            and Kwong, Sam 
            and Tao, Dacheng},  
    journal={IEEE Transactions on Image Processing},   
    title={An Underwater Image Enhancement Benchmark Dataset and Beyond},   
    year={2020},  
    volume={29},  
    number={},  
    pages={4376-4389},  
    doi={10.1109/TIP.2019.2955241}
}

@inproceedings{eriba2019kornia,
  author    = {E. Riba, D. Mishkin, D. Ponsa, E. Rublee and G. Bradski},
  title     = {Kornia: an Open Source Differentiable Computer Vision Library for PyTorch},
  booktitle = {Winter Conference on Applications of Computer Vision},
  year      = {2020},
  url       = {https://arxiv.org/pdf/1910.02190.pdf}
}

@inproceedings{islam2020suim,
  title={{Semantic Segmentation of Underwater Imagery: Dataset and Benchmark}},
  author={Islam, Md Jahidul and Edge, Chelsey and Xiao, Yuyang and Luo, Peigen and Mehtaz, 
              Muntaqim and Morse, Christopher and Enan, Sadman Sakib and Sattar, Junaed},
  booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2020},
  organization={IEEE/RSJ}
}

@article{8765346,
  author = {Z. {Cao} and G. {Hidalgo Martinez} and T. {Simon} and S. {Wei} and Y. A. {Sheikh}},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  title = {OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields},
  year = {2019}
}

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Acknowledgements

Future Releases