• Optics and Precision Engineering
  • Vol. 32, Issue 20, 3047 (2024)
Zheng XU, Jiaheng HE, Yanqi WANG, Xiaodong WANG*, and Tongqun REN
Author Affiliations
  • College of Mechanical Engineering, Dalian University of Technology, Dalian116081, China
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    DOI: 10.37188/OPE.20243220.3047 Cite this Article
    Zheng XU, Jiaheng HE, Yanqi WANG, Xiaodong WANG, Tongqun REN. End-to-end deblurring model for microscopic vision[J]. Optics and Precision Engineering, 2024, 32(20): 3047 Copy Citation Text show less
    Workflow of end-to-end deblurring model
    Fig. 1. Workflow of end-to-end deblurring model
    Process workflow of frequency domain
    Fig. 2. Process workflow of frequency domain
    Architecture of the blur discriminator.
    Fig. 3. Architecture of the blur discriminator.
    Architecture of deblurring network
    Fig. 4. Architecture of deblurring network
    Comparison between gaussian blur kernel size and optical defocus distance
    Fig. 5. Comparison between gaussian blur kernel size and optical defocus distance
    Images with different blurriness degrees
    Fig. 6. Images with different blurriness degrees
    Overall training process
    Fig. 7. Overall training process
    Comparison of restoration results
    Fig. 8. Comparison of restoration results
    Recovery of image with multiple blurriness
    Fig. 9. Recovery of image with multiple blurriness
    Experimental parts for precision measurement
    Fig. 10. Experimental parts for precision measurement
    类别精确率召回率F1值准确率
    清晰0.930.990.960.94
    轻度模糊0.990.990.99
    中度模糊0.880.970.92
    重度模糊0.970.840.90
    Table 1. Blurriness discrimination results
    组成部分选择
    傅里叶变换+极坐标转换
    低频剔除
    归一化

    清晰图片

    子数据集

    精确率0.931.000.980.990.77
    召回率0.990.990.971.001.00
    F1值0.961.000.970.990.87

    轻度模糊

    子数据集

    精确率1.000.970.990.900.51
    召回率0.990.900.960.940.44
    F1值0.990.930.980.920.48

    中度模糊

    子数据集

    精确率0.880.820.620.810.57
    召回率0.970.840.990.830.84
    F1值0.920.830.760.820.68

    重度模糊

    子数据集

    精确率0.970.850.970.910.96
    召回率0.840.890.730.850.96
    F1值0.900.870.830.880.96
    总数据集准确率0.940.910.890.900.69
    Table 2. Frequency domain processing module ablation experiment
    类别SSIMPSNR
    恢复模糊恢复模糊
    轻度模糊0.9830.96238.734.8
    中度模糊0.9730.81037.227.8
    重度模糊0.7710.48227.622.1
    均值0.9090.75134.528.2
    Table 3. Recovery result of corresponding branch networks for different degrees of blurriness
    低度模糊部分中度模糊部分重度模糊部分整体图像
    多重模糊0.9600.7890.4040.769
    图像恢复0.9630.8630.7060.864
    Table 4. SSIM scores of end-to-end deblurring model
    数据集类别图像SSIM
    σ多重模糊0.769
    图像恢复0.864
    σ0.25多重模糊0.792
    图像恢复0.852
    σ0.35多重模糊0.749
    图像恢复0.780
    Table 5. Recovery result on fine-tuned datasets
    精确率召回率F1
    本文分类器0.8770.8730.874
    ResNet180.8550.8470.849
    ResNet500.8700.8630.865
    VGG160.9280.9290.928
    Table 6. Comparison experiment of discriminator
    SSIMPSNR
    本文网络0.52023.1
    SRGAN70.24516.6
    SRResNet70.41520.5
    VDSR220.29117.6
    SRCNN230.32520.2
    Table 7. Comparison experiment of deblurring networks
    基准距离平均误差最大误差
    轻度模糊组模糊847.466.669.42
    恢复5.498.55
    中度模糊组模糊12.4512.69
    恢复3.625.44
    重度模糊组模糊12.4316.02
    恢复3.494.18
    Table 8. Comparison experiment of detection accuracy
    Zheng XU, Jiaheng HE, Yanqi WANG, Xiaodong WANG, Tongqun REN. End-to-end deblurring model for microscopic vision[J]. Optics and Precision Engineering, 2024, 32(20): 3047
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