• Acta Photonica Sinica
  • Vol. 51, Issue 3, 0301002 (2022)
Pengfei WU1、*, Huiliang WANG1, Sichen LEI1, and Shuai DANG2
Author Affiliations
  • 1School of Automation & Information Engineering,Xi'an University of Technology,Xi'an 710048,China
  • 2School of International Engineering,Xi'an University of Technology,Xi'an 710054,China
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    DOI: 10.3788/gzxb20225103.0301002 Cite this Article
    Pengfei WU, Huiliang WANG, Sichen LEI, Shuai DANG. Research on Spot Center Localization Algorithm in Atmospheric Turbulence Environment[J]. Acta Photonica Sinica, 2022, 51(3): 0301002 Copy Citation Text show less
    Principles of image detection algorithm flow chart
    Fig. 1. Principles of image detection algorithm flow chart
    Diagram of spot sliding compensation positioning
    Fig. 2. Diagram of spot sliding compensation positioning
    Phase screen simulation of atmospheric turbulence
    Fig. 3. Phase screen simulation of atmospheric turbulence
    Simulate the spot of Gaussian beam passing through the turbulent phase screen of different intensities
    Fig. 4. Simulate the spot of Gaussian beam passing through the turbulent phase screen of different intensities
    Positioning spacing between four algorithms in different intensity Gaussian noise
    Fig. 5. Positioning spacing between four algorithms in different intensity Gaussian noise
    Pixel intensity of spot image mask based on four positioning algorithms under different intensity gaussian noise
    Fig. 6. Pixel intensity of spot image mask based on four positioning algorithms under different intensity gaussian noise
    Laser communication link
    Fig. 7. Laser communication link
    10.2 km communication link
    Fig. 8. 10.2 km communication link
    2.4 km communication link
    Fig. 9. 2.4 km communication link
    Actual spot image captured in 10.2 km experiment
    Fig. 10. Actual spot image captured in 10.2 km experiment
    Intensity of the pixels in mask from 10.2 km spot image under different algorithms
    Fig. 11. Intensity of the pixels in mask from 10.2 km spot image under different algorithms
    Location distance between 10.2 km spot images based on different algorithms
    Fig. 12. Location distance between 10.2 km spot images based on different algorithms
    Actual spot image captured in 2.4 km experiment
    Fig. 13. Actual spot image captured in 2.4 km experiment
    Intensity of the pixels in mask from 2.4 km spot image under different algorithms
    Fig. 14. Intensity of the pixels in mask from 2.4 km spot image under different algorithms
    Location distance between 2.4 km spot images based on different algorithms
    Fig. 15. Location distance between 2.4 km spot images based on different algorithms

    Mode adaptive

    threshold method

    Adaptive

    threshold method

    Maximization of

    interclass

    variance method

    Iterative method
    Nonlinear weighted Barycenter algorithm0.000 969 90.006 6420.002 0170.002 017
    Barycenter algorithm0.005 2250.010 740.005 0020.005 002
    Table 1. Offsets of registration point from standard center under different algorithms/pixel
    2.4 km spot image10.2 km spot image
    MSEPSNRMSEPSNR
    Operation 12.915 343.484 00.159 456.105 1
    Operation 22.897 343.510 90.142 756.586 7
    Table 2. Effect analysis of spot processing
    Step-length L/pixel

    Pixel intensity/pixel

    R=30

    Pixel intensity/pixel

    R=60

    Average valueStandard deviationAverage valueStandard deviationAverage valueStandard deviation
    Sliding weighted Barycenter algorithm22.7512.784.247×1055.928×1041.328×1051.651×105
    Nonlinear weighted Barycenter algorithm25.2413.504.253×1055.975×1041.328×1051.646×105
    Barycenter algorithm24.5912.714.12×1056.366×1041.316×1051.631×105
    Centroid algorithm25.7712.733.96×1056.662×1041.291×1051.627×105
    Table 3. Effect analysis of 10.2 km spot processing
    Step-length L/pixel

    Pixel intensity/pixel

    R=30

    Pixel intensity/pixel

    R=60

    Average valueStandard deviationAverage valueStandard deviationAverage valueStandard deviation
    Sliding weighted Barycenter algorithm57.0035.993.269×1067.235×1054.642×1069.155×105
    Nonlinear weighted Barycenter algorithm63.1938.983.3×1067.243×1054.657×1069.137×105
    Barycenter algorithm60.3137.563.057×1067.24×1054.446×1069.177×105
    Centroid algorithm63.7736.522.807×1068.012×1054.212×1069.93×105
    Table 4. Effect analysis of 2.4 km spot processing
    Pengfei WU, Huiliang WANG, Sichen LEI, Shuai DANG. Research on Spot Center Localization Algorithm in Atmospheric Turbulence Environment[J]. Acta Photonica Sinica, 2022, 51(3): 0301002
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