• Opto-Electronic Engineering
  • Vol. 45, Issue 10, 170699 (2018)
Li Xuxu1、2、3、*, Li Xinyang1、2, and Wang Caixia1、2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: 10.12086/oee.2018.170699 Cite this Article
    Li Xuxu, Li Xinyang, Wang Caixia. Local adaptive threshold segmentation method for subapture spots of Shack-Hartmann sensor[J]. Opto-Electronic Engineering, 2018, 45(10): 170699 Copy Citation Text show less
    References

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    [2] Vargas J, González-Fernandez L, Quiroga J A, et al. Shack–Hartmann centroid detection method based on high dynamic range imaging and normalization techniques[J]. Applied Optics, 2010, 49(13): 2409–2416.

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    [9] Yin X M, Li X, Zhao L P, et al. Adaptive thresholding and dynamic windowing method for automatic centroid detection of digital Shack-Hartmann wavefront sensor[J]. Applied Optics, 2009, 48(32): 6088–6098.

    [10] Vyas A, Roopashree M B, Prasad B R. Centroid detection by Gaussian pattern matching in adaptive optics[J]. International Journal of Computer Applications, 2010, 1(26): 32–37.

    [11] Baker K L, Moallem M M. Iteratively weighted centroiding for Shack-Hartmann wave-front sensors[J]. Optics Express, 2007, 15(8): 5147–5159.

    [12] Ren J F, Rao C H, Li M Q. An adaptive threshold selection method for Hartmann-Shack wavefront sensor[J]. Opto- Electronic Engineering, 2002, 29(1): 1–5.

    [13] Li X X, Li X Y, Wang C X. Optimum threshold selection method of centroid computation for Gaussian spot[J]. Proceedings of SPIE, 2015, 9675: 967517.

    Li Xuxu, Li Xinyang, Wang Caixia. Local adaptive threshold segmentation method for subapture spots of Shack-Hartmann sensor[J]. Opto-Electronic Engineering, 2018, 45(10): 170699
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