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Rethinking Noise Synthesis and Modeling in Raw Denoising (ICCV2021)

Yi Zhang1, Hongwei Qin2, Xiaogang Wang1, Hongsheng Li1

1CUHK-SenseTime Joint Lab, 2SenseTime Research

Abstract

The lack of large-scale real raw image denoising dataset gives rise to challenges on synthesizing realistic raw image noise for training denoising models.However, the real raw image noise is contributed by many noise sources and varies greatly among different sensors. Existing methods are unable to model all noise sources accurately, and building a noise model for each sensor is also laborious. In this paper, we introduce a new perspective to synthesize noise by directly sampling from the sensor's real noise.It inherently generates accurate raw image noise for different camera sensors. Two efficient and generic techniques: pattern-aligned patch sampling and high-bit reconstruction help accurate synthesis of spatial-correlated noise and high-bit noise respectively. We conduct systematic experiments on SIDD and ELD datasets. The results show that (1) our method outperforms existing methods and demonstrates wide generalization on different sensors and lighting conditions. (2) Recent conclusions derived from DNN-based noise modeling methods are actually based on inaccurate noise parameters. The DNN-based methods still cannot outperform physics-based statistical methods.

Testing

The code has been tested with the following environment:

pytorch == 1.5.0
scikit-image == 0.16.2
scipy == 1.3.1
h5py 2.10.0 
  • Prepare the SIDD-Medium Dataset dataset.
  • Download the pretrained models and put them into the checkpoints folder.
  • Modify the default root of the SIDD dataset and run the command with the specific camera name (s6 | ip | gp)
python -u test.py --root SIDD_Medium/Data --camera s6

Noise parameters

The calibrated noise parameters for the SIDD dataset and the ELD dataset can be found in synthesize.py.

Citation

 @InProceedings{zhang2021rethinking,
        author    = {Zhang, Yi and Qin, Hongwei and Wang, Xiaogang and Li, Hongsheng},
        title     = {Rethinking Noise Synthesis and Modeling in Raw Denoising},
        booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
        month     = {October},
        year      = {2021},
        pages     = {4593-4601}
    }

Contact

Feel free to contact [email protected] if you have any questions.

Acknowledgments

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