• Acta Optica Sinica
  • Vol. 44, Issue 20, 2012003 (2024)
Chen Zhou, Xinjun Wan*, Xiaoxiao Wei, Zhenqiu Dai, and Xiaobin He
Author Affiliations
  • School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
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    DOI: 10.3788/AOS240841 Cite this Article Set citation alerts
    Chen Zhou, Xinjun Wan, Xiaoxiao Wei, Zhenqiu Dai, Xiaobin He. White Light Interferometry Fitting Algorithm Based on Region‐Directed Up‐Sampling[J]. Acta Optica Sinica, 2024, 44(20): 2012003 Copy Citation Text show less
    Structure of white light interferometry measurement system employing a stepper motor for vertical scanning
    Fig. 1. Structure of white light interferometry measurement system employing a stepper motor for vertical scanning
    Flowchart for implementing optimal hyperparameter selection using a search algorithm
    Fig. 2. Flowchart for implementing optimal hyperparameter selection using a search algorithm
    Principle of the morphology recovery algorithm based on region-directed up-sampling
    Fig. 3. Principle of the morphology recovery algorithm based on region-directed up-sampling
    Flow chart of morphology measurement algorithm
    Fig. 4. Flow chart of morphology measurement algorithm
    Simulated vertical scanning data. (a) Simulated scanning position; (b) scanning interval error; (c) white light interferometry image
    Fig. 5. Simulated vertical scanning data. (a) Simulated scanning position; (b) scanning interval error; (c) white light interferometry image
    Comparison between the fitting reconstruction signal and the ideal signal
    Fig. 6. Comparison between the fitting reconstruction signal and the ideal signal
    Comparison of step morphology reconstructed by different algorithms. (a) Centroid method; (b) proposed algorithm
    Fig. 7. Comparison of step morphology reconstructed by different algorithms. (a) Centroid method; (b) proposed algorithm
    Comparison of residual distribution of reconstructed surfaces under non-equidistant sampling. (a) Centroid method; (b) proposed algorithm
    Fig. 8. Comparison of residual distribution of reconstructed surfaces under non-equidistant sampling. (a) Centroid method; (b) proposed algorithm
    White light interferometry image of step plates collected in the experiment
    Fig. 9. White light interferometry image of step plates collected in the experiment
    Scanning position and scanning interval error of stepper motor. (a) Scanning position; (b) scanning interval error
    Fig. 10. Scanning position and scanning interval error of stepper motor. (a) Scanning position; (b) scanning interval error
    Comparison of reconstructed morphology and cross-section of standard steps by various algorithms. (a) Centroid method;
    Fig. 11. Comparison of reconstructed morphology and cross-section of standard steps by various algorithms. (a) Centroid method;
    Solution error. (a) Positioning error of the interpolated FFT envelope algorithm; (b) comparison of vertical profile curves solved by various algorithms
    Fig. 12. Solution error. (a) Positioning error of the interpolated FFT envelope algorithm; (b) comparison of vertical profile curves solved by various algorithms
    Algorithm

    Average

    height /nm

    Standard

    deviation /nm

    Error /%
    Centroid method385.94728.2623.513
    Proposed algorithm400.4531.1540.113
    Table 1. Comparison of solution results for a 400 nm step simulated five times by two different algorithms
    Algorithm

    Average

    height /nm

    Standard

    deviation /nm

    Error /

    %

    Centroid method946.40115.2441.417
    FFT envelope algorithm947.3157.4121.321
    Proposed algorithm956.5523.0460.359
    Table 2. Comparison of solution results for a 0.96 μm standard step by different algorithms
    Chen Zhou, Xinjun Wan, Xiaoxiao Wei, Zhenqiu Dai, Xiaobin He. White Light Interferometry Fitting Algorithm Based on Region‐Directed Up‐Sampling[J]. Acta Optica Sinica, 2024, 44(20): 2012003
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