OSA's Digital Library

Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 48, Iss. 32 — Nov. 10, 2009
  • pp: 6088–6098

Adaptive thresholding and dynamic windowing method for automatic centroid detection of digital Shack–Hartmann wavefront sensor

Yin Xiaoming, Li Xiang, Zhao Liping, and Fang Zhongping  »View Author Affiliations


Applied Optics, Vol. 48, Issue 32, pp. 6088-6098 (2009)
http://dx.doi.org/10.1364/AO.48.006088


View Full Text Article

Enhanced HTML    Acrobat PDF (1709 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

A Shack–Hartmann wavefront sensor (SWHS) splits the incident wavefront into many subsections and transfers the distorted wavefront detection into the centroid measurement. The accuracy of the centroid measurement determines the accuracy of the SWHS. Many methods have been presented to improve the accuracy of the wavefront centroid measurement. However, most of these methods are discussed from the point of view of optics, based on the assumption that the spot intensity of the SHWS has a Gaussian distribution, which is not applicable to the digital SHWS. In this paper, we present a centroid measurement algorithm based on the adaptive thresholding and dynamic windowing method by utilizing image processing techniques for practical application of the digital SHWS in surface profile measurement. The method can detect the centroid of each focal spot precisely and robustly by eliminating the influence of various noises, such as diffraction of the digital SHWS, unevenness and instability of the light source, as well as deviation between the centroid of the focal spot and the center of the detection area. The experimental results demonstrate that the algorithm has better precision, repeatability, and stability compared with other commonly used centroid methods, such as the statistical averaging, thresholding, and windowing algorithms.

© 2009 Optical Society of America

OCIS Codes
(100.5070) Image processing : Phase retrieval
(120.3940) Instrumentation, measurement, and metrology : Metrology

ToC Category:
Instrumentation, Measurement, and Metrology

History
Original Manuscript: May 13, 2009
Revised Manuscript: September 24, 2009
Manuscript Accepted: September 28, 2009
Published: November 2, 2009

Citation
Xiaoming Yin, Xiang Li, Liping Zhao, and Zhongping Fang, "Adaptive thresholding and dynamic windowing method for automatic centroid detection of digital Shack-Hartmann wavefront sensor," Appl. Opt. 48, 6088-6098 (2009)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-48-32-6088


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. T. J. Kane, B. M. Welsh, and C. S. Gardner, “Wave front detector optimization for laser guided adaptive telescope,” Proc. SPIE 1114, 160-171 (1989).
  2. G. Cao and X. Yu, “Accuracy analysis of a Hartmann-Shack wavefront sensor operated with a faint object,” Opt. Eng. 33, 2331-2335 (1994). [CrossRef]
  3. R. Irwan and R. G. Lane, “Analysis of optimal centroid estimation applied to Shack-Hartmann sensing,” Appl. Opt. 38, 6737-6743 (1999). [CrossRef]
  4. A. Zhang, C. Rao, Y. Zhang, and W. Jiang, “Sampling error analysis of Shack-Hartmann wavefront sensor with variable subaperture pixels,” J. Mod. Opt. 51, 2267-2278 (2004).
  5. S. K. Park and S. H. Baik, “A study on a fast measuring technique of wavefront using a Shack-Hartmann sensor,” Opt. Laser Technol. 34, 687-684 (2002). [CrossRef]
  6. J. F. Ren, C. H. Rao, and Q. M. Li, “An adaptive threshold selection method for Hartmann-Shack wavefront sensor,” Opto-electron. Eng. 29, 1-5 (2002).
  7. S. H. Baik, S. K. Park, C. J. Kim, and B. Cha, “A center detection algorithm for Shack-Hartmann sensor,” Opt. Laser Technol. 39, 262-267 (2007). [CrossRef]
  8. P. Arulmozhivarman, L. P. Kumar, and A. R. Ganesan, “Measurement of moments for centroid estimation in Shack-Hartmann wavefront sensor--a wavelet-based approach and comparison with other methods,” Optik (Jena) 117, 82-87 (2006). [CrossRef]
  9. S. A. Sallberg, B. M. Welsh, and M. C. Roggemann, “Maximum a posteriori estimation of wave-front slopes using a Shack-Hartmann wave-front sensor,” J. Opt. Soc. Am. A 14, 1347-1354 (1997). [CrossRef]
  10. M. A. van Dam and R. G. Lane, “Wave-front slope estimation,” J. Opt. Soc. Am. A 17, 1319-1324 (2000). [CrossRef]
  11. J. Ares and J. Arines, “Influence of thresholding on centroid statistics: full analytical description,” Appl. Opt. 43, 5796-5805 (2004). [CrossRef] [PubMed]
  12. Z. L. Jiang, S. S. Gong, and Y. Dai, “Numerical study of centroid detection accuracy for Shack-Hartmann wavefront sensor,” Opt. Laser Technol. 38, 614-619 (2006). [CrossRef]
  13. L. P. Zhao, N. Bai, X. Li, L. S. Ong, Z. P. Fang, and A. K. Asundi, “Efficient implementation of SLM as diffractive optical microlens array in digital Shack Hartman wavefront sensor,” Appl. Opt. 45, 90-94 (2006). [CrossRef] [PubMed]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited