Acta Optica Sinica, Volume. 43, Issue 3, 0312005(2023)

Sub-Spot Centroid Extraction Algorithm Based on Noise Model Transformation

Chunlu Chen1,2,3, Wang Zhao1,2、**, Mengmeng Zhao1,2,3, Shuai Wang1,2、*, Chensi Zhao1,2,3, and Kangjian Yang1,2
Author Affiliations
  • 1Key Laboratory on Adaptive Optics, Chinese Academy of Sciences, Chengdu 610209,Sichuan, China
  • 2Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, Sichuan, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
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    Figures & Tables(18)
    Flow chart of proposed method
    Flow chart of NFBM3D algorithm
    Detection results of beam wavefront. (a) Non-uniform distribution of near-field light intensity; (b) spot array image with low signal-to-noise ratio; (c) peak signal-to-noise ratio for each sub-aperture
    Spot array images before and after denoising. (a) Clear image; (b) image with noise; (c) image after NFBM3D denoising
    Average CEE of different methods under different peak signal-to-noise ratios
    CEE of different methods under non-uniformly varying light intensity
    Probability density functions of CEE of different methods under different peak signal-to-noise ratios. (a) Peak signal-to-noise ratio of 3-4; (b) peak signal-to-noise ratio of 4-5
    CEE after pre-processing with different denoising methods under varying light intensity
    Restoration wavefront and restoration residual in absence of noise. (a) Input wavefront; (b) recovery wavefront without noise; (c) recovery residual without noise
    Wavefront recovery residuals after centroid extraction by different methods. (a) TkCoG; (b) Windowing; (c) Adathreshold;(d) NLM; (e) BM3D; (f) NFBM3D
    Experimental system. (a) Schematic diagram; (b) physical map
    Detection results of beam wavefront. (a) Acquired spot array image; (b) peak signal-to-noise ratio of each sub-aperture
    Estimation method for signal-to-noise ratio. (a) Enlarged view of single clear sub-spot; (b) enlarged image of single noisy sub-spot
    CEE of each method
    Input wavefront and recovery wavefronts obtained by different centroid extraction methods. (a) Input wavefront; (b) TkCoG;(c) Windowing; (d) Adathreshold; (e) NLM; (f) VSTBM3D; (g) NFBM3D
    Recovery residuals obtained by different centroid extraction methods. (a) TkCoG; (b) Windowing; (c) Adathreshold; (d) NLM;(e) VSTBM3D; (f) NFBM3D
    • Table 1. Simulation parameters

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      Table 1. Simulation parameters

      ParameterWavelength /nmD /r0Number of sub-aperturesSub-aperture size /μmFocal length /mmPixel length /μm
      Value10641016×1627011.515
    • Table 2. Experimental parameters

      View table

      Table 2. Experimental parameters

      ParameterWavelength /nmPixel size /μmNumber of sub-aperturesTarget pixelNumber of effective sub-aperturesFocal length /cm
      Value6356.416×16992×9921924.23
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    Chunlu Chen, Wang Zhao, Mengmeng Zhao, Shuai Wang, Chensi Zhao, Kangjian Yang. Sub-Spot Centroid Extraction Algorithm Based on Noise Model Transformation[J]. Acta Optica Sinica, 2023, 43(3): 0312005

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Jul. 25, 2022

    Accepted: Aug. 25, 2022

    Published Online: Feb. 13, 2023

    The Author Email: Zhao Wang (zw_2017@foxmail.com), Wang Shuai (wangshuai@ioe.ac.cn)

    DOI:10.3788/AOS221522

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