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Laser & Optoelectronics Progress, Volume. 57, Issue 22, 221018(2020)

Image Denoising Based on Asymmetric Convolutional Neural Networks

Jianwang Gan1, Yun Sha1、*, and Guoying Zhang2
Author Affiliations
  • 1School of Information Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China
  • 2School of Mechanical Electronic & Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China;
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    AbstractGet PDF(in Chinese)
    Figures&Tables (11)
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    References (17)
    Cited By (1)
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    Figures & Tables(11)
    Partially synthesized noise images.

    Fig. 1. Partially synthesized noise images.

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    CBDNet model

    Fig. 2. CBDNet model

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    CBDNet denoising subnet architecture

    Fig. 3. CBDNet denoising subnet architecture

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    UNet++ architecture

    Fig. 4. UNet++ architecture

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    Improved network model

    Fig. 5. Improved network model

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    Denoising results of image 1. (a) Original image; (b) noise image; (c) CBDNet; (d) improved CBDNet

    Fig. 6. Denoising results of image 1. (a) Original image; (b) noise image; (c) CBDNet; (d) improved CBDNet

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    Denoising results of image 2. (a) Original image; (b) noise image; (c) CBDNet; (d) improved CBDNet

    Fig. 7. Denoising results of image 2. (a) Original image; (b) noise image; (c) CBDNet; (d) improved CBDNet

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    Denoising results of image 3. (a) Original image; (b) noise image; (c) CBDNet; (d) improved CBDNet

    Fig. 8. Denoising results of image 3. (a) Original image; (b) noise image; (c) CBDNet; (d) improved CBDNet

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    • Table 1. PSNR of 10 images

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      Table 1. PSNR of 10 images

      No.CBDNetImproved CBDNet
      135.76972035.880955
      231.46179430.128640
      336.20212036.103760
      433.20525733.806810
      535.03499234.901047
      638.66932740.513270
      737.77080537.781620
      834.80051834.688103
      934.61019534.964275
      1034.23290334.225975
      Mean value35.17576235.299446

    • Table 2. SSIM of 10 images

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      Table 2. SSIM of 10 images

      No.CBDNetImproved CBDNet
      10.941740700.94231653
      20.963752570.96220344
      30.972951230.97360283
      40.975487050.97699260
      50.977546300.97723440
      60.979628560.97987250
      70.982511040.98210240
      80.985826700.98583820
      90.969948600.97106440
      100.979355630.97972226
      Mean value0.972874800.97309494

    • Table 3. Mean of PSNR and SSIM

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      Table 3. Mean of PSNR and SSIM

      TypeBM3DCBDNetImproved CBDNet
      PSNR35.0035.20035.400
      SSIM0.860.9720.973
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    Jianwang Gan, Yun Sha, Guoying Zhang. Image Denoising Based on Asymmetric Convolutional Neural Networks[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221018

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    Paper Information

    Category: Image Processing

    Received: Apr. 2, 2020

    Accepted: Apr. 21, 2020

    Published Online: Nov. 5, 2020

    The Author Email: Sha Yun (shayun@bipt.edu.cn)

    DOI:10.3788/LOP57.221018

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology