Acta Optica Sinica, Volume. 45, Issue 11, 1111003(2025)

Depth Estimation Based on Single-Lens Point Spread Function Regulation

Zaiwu Sun1, Fanjiao Tan1, Pengliang Yu2, Zongling Li1, Rongshuai Zhang1, Changjian Yang1, and Qingyu Hou1、*
Author Affiliations
  • 1Research Center for Space Optical Engineering, School of Astronautics, Harbin Institute of Technology, Harbin 150001, Heilongjiang , China
  • 2Harbin Xinguang Optic-Electronics Technology Co., Ltd, Harbin 150036, Heilongjiang , China
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    Figures & Tables(14)
    Framework of end-to-end design for single-lens depth estimation system
    Schematic diagram of camera imaging range
    Simulated images of the same scene using different imaging models
    U-Net structure used in single-lens depth estimation system
    PSFs for different FOVs and depths
    Point spread functions of different models
    Visual comparison of proposed method with other methods on NYU Depth V2 dataset
    Comparison of depth estimation performance of models at different depths. (a) Prediction depth of each model at different depths; (b) MAE between predicted and estimated values at different depths
    Visualization comparison of ablation experiment results of proposed method
    Depth estimation performance of model on FlyingThings3D
    • Table 1. Comparison between different imaging models and rendering method

      View table

      Table 1. Comparison between different imaging models and rendering method

      MethodPSNRSSIM
      Thin lens model25.190.811
      Our model28.680.899
    • Table 2. Quantitative comparison of proposed method with other methods on NYU Depth V2 dataset

      View table

      Table 2. Quantitative comparison of proposed method with other methods on NYU Depth V2 dataset

      MethodMAERMSEESilogδ<1.25δ<1.252δ<1.253
      DFD120.2060.2990.0190.9140.9360.965
      Wu et al.200.1970.2780.0170.9240.9450.962
      Ikoma et al.260.1710.2590.0160.9380.9630.990
      Qian et al.370.2870.3960.0330.8660.9730.995
      Ours0.1550.2310.0140.9470.9750.994
    • Table 3. Quantitative comparison of ablation experimental results of proposed methods

      View table

      Table 3. Quantitative comparison of ablation experimental results of proposed methods

      MethodMAERMSEESilogδ<1.25δ<1.252δ<1.253
      With initial single lens0.2420.3160.0200.9150.9410.966
      Without preprocessing method0.1570.2400.0150.9430.9710.994
      With preprocessing method0.1550.2310.0140.9470.9750.998
    • Table 4. Quantitative evaluation results of model on FlyingThings3D

      View table

      Table 4. Quantitative evaluation results of model on FlyingThings3D

      MethodMAERMSEESilogδ<1.25δ<1.252δ<1.253
      Without preprocessing method0.2260.3830.0230.9270.9770.985
      With preprocessing method0.2210.3770.0240.9290.9740.987
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    Zaiwu Sun, Fanjiao Tan, Pengliang Yu, Zongling Li, Rongshuai Zhang, Changjian Yang, Qingyu Hou. Depth Estimation Based on Single-Lens Point Spread Function Regulation[J]. Acta Optica Sinica, 2025, 45(11): 1111003

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    Paper Information

    Category: Imaging Systems

    Received: Feb. 26, 2025

    Accepted: Apr. 15, 2025

    Published Online: Jun. 23, 2025

    The Author Email: Qingyu Hou (houqingyu@126.com)

    DOI:10.3788/AOS250660

    CSTR:32393.14.AOS250660

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