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Laser & Optoelectronics Progress, Volume. 57, Issue 16, 161020(2020)

Research on Depth Image Repair Algorithm Based on Improved Bilateral Filter

Yilin Yang*, Jiying Li, Yan Wang, and Yongqian Yu
Author Affiliations
  • School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (7)
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    References (17)
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    Figures & Tables(7)
    Flow chart of proposed algorithm

    Fig. 1. Flow chart of proposed algorithm

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    Registration results of RGB images and depth images. (a) RGB images; (b) depth images

    Fig. 2. Registration results of RGB images and depth images. (a) RGB images; (b) depth images

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    Experimental verification results. (a) Original RGB image; (b) original depth image; (c) verification results of proposed algorithm

    Fig. 3. Experimental verification results. (a) Original RGB image; (b) original depth image; (c) verification results of proposed algorithm

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    Repair results of artificially added holes. (a) Original RGB images; (b) original depth images; (c) repair results of GF algorithm; (d) repair results of JBF algorithm; (e) repair results of proposed algorithm

    Fig. 4. Repair results of artificially added holes. (a) Original RGB images; (b) original depth images; (c) repair results of GF algorithm; (d) repair results of JBF algorithm; (e) repair results of proposed algorithm

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    Repair results of natural holes. (a) Original RGB images; (b) original depth images; (c) repair results of GF algorithm and its local details; (d) repair results of JBF algorithm and its local details; (e) repair results of proposed algorithm and its local details

    Fig. 5. Repair results of natural holes. (a) Original RGB images; (b) original depth images; (c) repair results of GF algorithm and its local details; (d) repair results of JBF algorithm and its local details; (e) repair results of proposed algorithm and its local details

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    • Table 1. RMSE of each depth image repair algorithm based on Middlebury standard library

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      Table 1. RMSE of each depth image repair algorithm based on Middlebury standard library

      MethodDollsMoebiusLaundry
      GF algorithm3.60143.89744.9055
      JBF algorithm3.47042.71463.5219
      Proposed algorithm3.41292.54772.8112
      R1 /%5.2334.6342.69
      R2 /%1.666.1520.18

    • Table 2. PSNR of each depth image repair algorithm based on Middlebury standard library

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      Table 2. PSNR of each depth image repair algorithm based on Middlebury standard library

      MethodDollsMoebiusLaundry
      GF algorithm37.001336.315434.3172
      JBF algorithm37.323139.456737.1952
      Proposed algorithm37.468440.007939.1531
      P1 /%1.26210.16814.092
      P2 /%0.3891.3975.264
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    Yilin Yang, Jiying Li, Yan Wang, Yongqian Yu. Research on Depth Image Repair Algorithm Based on Improved Bilateral Filter[J]. Laser & Optoelectronics Progress, 2020, 57(16): 161020

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    Paper Information

    Category: Image Processing

    Received: Dec. 10, 2019

    Accepted: Jan. 16, 2020

    Published Online: Aug. 5, 2020

    The Author Email: Yang Yilin (2235931584@qq.com)

    DOI:10.3788/LOP57.161020

    Topics

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