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Acta Optica Sinica, Volume. 40, Issue 5, 0510002(2020)

Depth Estimation Method of Light Field Image Based on Occlusion Scene

Xiaomin Liu*, Mengzhu Du, Zhibang Ma, Yunfei Zhu, Pengbo Chen, and Fengying Ma
Author Affiliations
  • School of Physics, Zhengzhou University, Zhengzhou, Henan 450001, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (11)
    Equations (0)
    References (13)
    Cited By (7)
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    Paper Information
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    Figures & Tables(11)
    Imaging model of Lytro camera

    Fig. 1. Imaging model of Lytro camera

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    Diagram of 4D light field

    Fig. 2. Diagram of 4D light field

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    Multi-view image

    Fig. 3. Multi-view image

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    Digital refocusing principle

    Fig. 4. Digital refocusing principle

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    Effect comparison diagram. (a) Constrained adaptive defocus depth map; (b) traditional defocus depth map

    Fig. 5. Effect comparison diagram. (a) Constrained adaptive defocus depth map; (b) traditional defocus depth map

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    Defocus depth map and consistent depth map. (a) Constrained adaptive defocus depth map; (b) constrained angle entropy depth map

    Fig. 6. Defocus depth map and consistent depth map. (a) Constrained adaptive defocus depth map; (b) constrained angle entropy depth map

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    Map results. (a) Initial depth map; (b) confidence map; (c) edge detection result; (d) final depth estimation result

    Fig. 7. Map results. (a) Initial depth map; (b) confidence map; (c) edge detection result; (d) final depth estimation result

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    Depth estimation results of MonasRoom light field reference dataset. (a) MonasRoom central perspective image; (b) GT value; (c) the proposed method; (d) method in Ref. [13]; (e) method in Ref.[8]; (f) method in Ref.[5]

    Fig. 8. Depth estimation results of MonasRoom light field reference dataset. (a) MonasRoom central perspective image; (b) GT value; (c) the proposed method; (d) method in Ref. [13]; (e) method in Ref.[8]; (f) method in Ref.[5]

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    Depth estimation results of Budden light field reference dataset. (a) Budden central perspective image; (b) GT value; (c) the proposed method; (d) method in Ref.[13]; (e) method in Ref.[8]; (f) method in Ref.[5]

    Fig. 9. Depth estimation results of Budden light field reference dataset. (a) Budden central perspective image; (b) GT value; (c) the proposed method; (d) method in Ref.[13]; (e) method in Ref.[8]; (f) method in Ref.[5]

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    Depth estimation results of 5×5 view light field images taken by Lytro

    Fig. 10. Depth estimation results of 5×5 view light field images taken by Lytro

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    • Table 1. EMS comparison

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      Table 1. EMS comparison

      MethodMonasRoomBuddenMedieval
      Method in Ref.[13]0.003380.009560.01272
      Proposed method0.002110.004130.01210
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    Xiaomin Liu, Mengzhu Du, Zhibang Ma, Yunfei Zhu, Pengbo Chen, Fengying Ma. Depth Estimation Method of Light Field Image Based on Occlusion Scene[J]. Acta Optica Sinica, 2020, 40(5): 0510002

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    Paper Information

    Category: Image Processing

    Received: Sep. 3, 2019

    Accepted: Nov. 18, 2019

    Published Online: Mar. 10, 2020

    The Author Email: Xiaomin Liu (liuxmamara@zzu.edu.cn)

    DOI:10.3788/AOS202040.0510002

    Topics

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