Volume 43 Issue 9
Oct.  2014
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Zhao Feifei, Huang Wei, Xu Weicai, Yang Tianxing. Optimization method for the centroid sensing of Shack-Hartmann wavefront sensor[J]. Infrared and Laser Engineering, 2014, 43(9): 3005-3009.
Citation: Zhao Feifei, Huang Wei, Xu Weicai, Yang Tianxing. Optimization method for the centroid sensing of Shack-Hartmann wavefront sensor[J]. Infrared and Laser Engineering, 2014, 43(9): 3005-3009.

Optimization method for the centroid sensing of Shack-Hartmann wavefront sensor

  • Received Date: 2014-01-11
  • Rev Recd Date: 2014-02-13
  • Publish Date: 2014-09-25
  • In order to improve the centroid sensing accuracy of spot image of Shack-Hartmann wavefront sensor (S-H WFS), the error sources of centroid detection were discussed in the paper. The influence of detection window, threshold selection and centroid algorithm on centroid detection accuracy was analyzed. On this basis, detecting window selection method based on template match and adaptive threshold selection method based on single spot were proposed. The methods proposed in this paper were combined with the center of weight algorithm for improving the centroid detection accuracy. The accuracy with the comprehensive method increases 40% comparing with traditional method when signal-to-noise ratio(SNR) of the spot image of S-H WFS is more than 3. The methods was applied to a S-H WFS working in visible spectrum, the results showed that maximum centroid departure decreased from 0.83 pixel to 0.15 pixel. The work in this paper has a high value of practical application.
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    [4] Wang Wei, Chen Huaixin. New method for centroid detectingof focal spot based on optimizing detecting window[J]. HighPower Laser and Particle Beams, 2006, 18(8): 1249-1252.(in Chinese)王薇, 陈怀新. 基于优化探测窗口的光斑质心探测方法[J]. 强激光与粒子束, 2006, 18(8): 1249-1252.
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    [6] Xia Mingliang, Li Chao, Liu Zhaonan, et al. Adaptivethreshold selection method for Shack-Hartmann wavefrontsensors [J]. Opt Precision Eng, 2010 18 (2): 334-340. (inChinese)夏明亮, 李抄, 刘肇南, 等. Shack-Hartmann 波前传感器图像自适应阈值的选取[J]. 光学精密工程, 2010, 18(2): 334-340.
    [7] Wang Xinyue, Gao Xuhui. Image segmentation method ofself-adapting threshold [J]. Infrared and Laser Engineering,2006, 35(S4): 167-171. (in Chinese)王歆癑, 高旭辉. 一种自适应阈值分割方法[J]. 红外与激光工程, 2006, 35(S4): 167-171.
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    [11] Shen Feng, Jiang Wenhan. The threshold method improvingthe centroid detection accuracy of a Hartmann-shackwavefront sensor [J]. Opto-Electronic Engineering, 1997, 24(3): 1-8. (in Chinese)沈锋, 姜文汉. 提高Hartmann 波前传感器质心探测精度的阈值方法[J]. 光电工程, 1997, 24(3): 1-8.
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Optimization method for the centroid sensing of Shack-Hartmann wavefront sensor

  • 1. State Key Laboratory of Applied Optics,Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun 130033,China;
  • 2. University of Chinese Academy of Sciences,Beijing 100049,China

Abstract: In order to improve the centroid sensing accuracy of spot image of Shack-Hartmann wavefront sensor (S-H WFS), the error sources of centroid detection were discussed in the paper. The influence of detection window, threshold selection and centroid algorithm on centroid detection accuracy was analyzed. On this basis, detecting window selection method based on template match and adaptive threshold selection method based on single spot were proposed. The methods proposed in this paper were combined with the center of weight algorithm for improving the centroid detection accuracy. The accuracy with the comprehensive method increases 40% comparing with traditional method when signal-to-noise ratio(SNR) of the spot image of S-H WFS is more than 3. The methods was applied to a S-H WFS working in visible spectrum, the results showed that maximum centroid departure decreased from 0.83 pixel to 0.15 pixel. The work in this paper has a high value of practical application.

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