Journal of Applied Optics, Volume. 45, Issue 5, 937(2024)

General progressive unsupervised image enhancement method focusing on value aware

Aiguo ZHOU1, Jilin ZHAO1、*, Shan AN2, and Changhong FU1
Author Affiliations
  • 1School of Mechanical Engineering, Tongji University, Shanghai 201804, China
  • 2Beijing Jingdong Tuoxian Technology Co.,Ltd., Beijing 100176, China
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    Figures & Tables(11)
    General progressive unsupervised image enhancement method focusing on value aware
    Structure diagram of VAPEN model
    Schematic of progressive enhancement strategy
    Comparison of actual enhancement effect between proposed method and other enhancers on LOL test set
    Performance evaluation experiment of SiamAPN tracker with proposed method
    Visualization images of object tracking process and error curves for center position
    Ablation experiment of iteration number
    • Table 1. Detailed structure parameters of VAPEN model

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      Table 1. Detailed structure parameters of VAPEN model

      阶段输入通道输出通道卷积核激活函数上/下采样
      预编码Conv0-11163×3--
      Conv0-216163×3Sigmoid-
      编码Conv1-116163×3-下采样
      Conv1-216163×3Sigmoid-
      Conv2-116163×3-下采样
      Conv2-216163×3Sigmoid-
      Conv3-116163×3-下采样
      Conv3-216163×3Sigmoid-
      解码Conv1-132163×3-上采样
      Conv1-216163×3Sigmoid-
      Conv2-132163×3-上采样
      Conv2-216163×3Sigmoid-
      Conv3-132163×3-上采样
      Conv3-21613×3Tanh-
    • Table 2. Quantitative evaluation results on authoritative benchmark

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      Table 2. Quantitative evaluation results on authoritative benchmark

      方法PSNRSSIM
      SCI_E9.5800.388
      RUAS_U11.3090.483
      RRDNet11.3780.519
      DarkLighter13.7640.613
      SCI_D13.8060.597
      SCI_M14.7840.618
      DCE14.8610.666
      DCE++15.2490.675
      RUAS_D16.1460.578
      RUAS_L16.4050.701
      RetinexNet16.7740.539
      LIME16.9200.620
      本文方法17.6100.618
    • Table 3. Model parameters and runtime efficiency ms

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      Table 3. Model parameters and runtime efficiency ms

      方法SCIRetinexNetRRDNetDarkLighterDCEDCE++RUASLIME本文方法
      参数量25813587391281677476879416105613438-35057
      处理时间0.5566.516.612.5212.382.0817.1694.44.45
    • Table 4. Ablation experiment

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      Table 4. Ablation experiment

      亮度约束项平滑项保真项PSNRSSIM
      13.9950.471
      6.5230.019
      7.5530.159
      16.6950.593
      13.9940.472
      7.5300.156
      17.6100.618
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    Aiguo ZHOU, Jilin ZHAO, Shan AN, Changhong FU. General progressive unsupervised image enhancement method focusing on value aware[J]. Journal of Applied Optics, 2024, 45(5): 937

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    Paper Information

    Category:

    Received: Mar. 26, 2024

    Accepted: --

    Published Online: Dec. 20, 2024

    The Author Email: Jilin ZHAO (符长虹)

    DOI:10.5768/JAO202445.0502001

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