Acta Optica Sinica, Volume. 40, Issue 1, 0111027(2020)

Synthetic-Aperture Occlusion Removal Algorithm Using Microlens Array

Wentong Qian1,2, hui Li1,2,3、*, and Yuntao Wu1,2
Author Affiliations
  • 1School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan, Hubei 430205, China
  • 2Hubei Key Laboratory of Intelligent Robot, Wuhan, Hubei 430205, China
  • 3School of Chemistry and Chemical Engineering, Huazhong University of Science & Technology, Wuhan, Hubei 430074, China;
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    Figures & Tables(11)
    Flow chart of synthetic-aperture occlusion removal algorithm based on microlens array
    Light field sampling based on microlens array
    Principle of refocusing
    Scene diagram
    Original image
    Processing images of algorithm for each step. (a) Sampling image of microlens; (b) binary extracted occlusion grid; (c) result without using synthetic aperture; (d) occlusion removal result
    Results of three algorithms. (a) Microlens synthetic aperture algorithm; (b) multi-cue fusion extraction depth algorithm; (c) prior information matching based algorithm
    Images processed by three algorithms. (a)-(c) Binarization images of Figs. 7(a)-(c); (d)-(f) contour extraction images of Figs. 7(a)-(c)
    • Table 1. Parameters of MLA150-5C microlens array

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      Table 1. Parameters of MLA150-5C microlens array

      PitchRadius of curvatureFocal lengthPupil
      0.15 mm2.4 mm5.2 mmChrome
    • Table 2. Average gradient value of results of three algorithms

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      Table 2. Average gradient value of results of three algorithms

      GroupAlgorithmAveragegradient
      Synthetic aperture of microlens array0.0476
      Group1Multi-cue fusion extraction depth[4]0.0212
      Base on regional prior information[6]0.0182
      Synthetic aperture of microlens array0.0324
      Group2Multi-cue fusion extraction depth[4]0.0238
      Base on regional prior information[6]0.0129
      Synthetic aperture of microlens array0.0387
      Group3Multi-cue fusion extraction depth[4]0.0232
      Base on regional prior information[6]0.0202
    • Table 3. Comparison of image qualities obtained by different algorithms

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      Table 3. Comparison of image qualities obtained by different algorithms

      GroupAlgorithmBrennerTenengradSMDSMD2Energy
      Synthetic aperture of microlens array21.638346.2426187.63924.8237102.392
      Group1Multi-cue fusion extraction depth[4]17.2057297.1573121.83294.792382.4373
      Base on regional prior information[6]9.1939240.038183.23983.490842.9048
      Synthetic aperture of microlens array32.814392.8423239.84785.2394124.324
      Group2Multi-cue fusion extraction depth[4]28.932242.7176131.23664.308258.6362
      Base on regional prior information[6]8.2309224.853978.49052.074539.7248
      Synthetic aperture of microlens array27.8409279.804595.73566.013997.4584
      Group3Multi-cue fusion extraction depth[4]15.897239.740182.31475.225361.4399
      Base on regional prior information[6]9.2347134.562963.47594.826957.2825
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    Wentong Qian, hui Li, Yuntao Wu. Synthetic-Aperture Occlusion Removal Algorithm Using Microlens Array[J]. Acta Optica Sinica, 2020, 40(1): 0111027

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    Paper Information

    Category: Special Issue on Computational Optical Imaging

    Received: Sep. 2, 2019

    Accepted: Oct. 21, 2019

    Published Online: Jan. 6, 2020

    The Author Email: Li hui (lihui00317@163.com)

    DOI:10.3788/AOS202040.0111027

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