Laser & Optoelectronics Progress, Volume. 59, Issue 4, 0410002(2022)

Automatic Background Blurring Algorithm Based on Image Perception and Segmentation

Chengmin Liu, Wujian Ye*, and Yijun Liu
Author Affiliations
  • School of Information Engineering, Guangdong University of Technology, Guangzhou , Guangdong 510006, China
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    Figures & Tables(14)
    System framework diagram
    Auxiliary image outputs. (a) Original image; (b) focus image; (c) depth of field image; (d) Mask corresponding to vehicle on left; (e) Mask corresponding to vehicle on right
    Diagram of ResNet-18 network structure
    Filter out Mask that is too small. (a) Original image; (b) (c) Masks before filtering; (d) Mask after filtering
    Filter out overlapping Masks. (a) Original image; (b)‒(e) Masks before filtering; (f) (g) Masks after filtering
    Background blur images. (a) Background blur image after simple fusion; (b) background blur image after edge optimization
    Comparison of results of experiment 1. (a1)(a2) Original image; (b1)(b2) Mask R-CNN; (c1)(c2) YOLACT
    Comparison of results of experiment 2. (a1)(a2) No edge optimization; (b1) (b2) Poisson fusion edge optimization; (c1)(c2) mean filter edge optimization
    Comparison of results of experiment 3. (a1) (a2) Original images; (b1)(b2) small filter cores; (c1)(c2) moderate filter cores; (d1) (d2) large filter cores
    Comparison of results of experiment 3. (a) Depth of field image; (b1)(b2) original images; (c1) without sense of hierarchy (auto focus); (c2) without sense of hierarchy (independent selection); (d1) with sense of hierarchy (auto focus); (d2) with sense of hierarchy (independent selection)
    Comparison of results of experiment 5. (a) Original image; (b) autofocus mode of our method; (c) independent selection mode of our method; (d) Huawei P20; (e) iPhone XR
    Comparison of results of experiment 6. (a) Original image; (b) our method; (c) method proposed by Yang et al.; (d) method proposed by Xiong et al.; (e) method proposed by Purohit et al.; (f) method proposed by Dutta et al.; (g) method proposed by Zheng et al.
    • Table 1. Comparison of PSNR

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      Table 1. Comparison of PSNR

      AlgorithmNo edge tuningPoisson fusion edge tuningFiltering edge tuning
      PSNR22.7522.4322.80
    • Table 2. Comparison of subjective evaluation of blur effects of several algorithms

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      Table 2. Comparison of subjective evaluation of blur effects of several algorithms

      AlgorithmYang et al.Xiong et al.Purohit et al.Dutta et al.Zheng et al.Our paper
      Score6.945.286.786.086.437.27
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    Chengmin Liu, Wujian Ye, Yijun Liu. Automatic Background Blurring Algorithm Based on Image Perception and Segmentation[J]. Laser & Optoelectronics Progress, 2022, 59(4): 0410002

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    Paper Information

    Category: Image Processing

    Received: Jan. 25, 2021

    Accepted: Mar. 19, 2021

    Published Online: Jan. 25, 2022

    The Author Email: Wujian Ye (yewjian@126.com)

    DOI:10.3788/LOP202259.0410002

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