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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 44, Iss. 18 — Jun. 20, 2005
  • pp: 3646–3653

Extracting mode components in laser intensity distribution by independent component analysis

Hai-Tao Fang and De-Shuang Huang  »View Author Affiliations


Applied Optics, Vol. 44, Issue 18, pp. 3646-3653 (2005)
http://dx.doi.org/10.1364/AO.44.003646


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Abstract

With increasingly sophisticated laser applications in industry and science, a reliable method to characterize the intensity distribution of the laser beam has become a more and more important task. However, traditional optic and electronic methods can offer only a laser beam intensity profile but, cannot separate the main mode components in the laser beam intensity distribution. Recently, independent component analysis has been a surging and developing method in which the goal is to find a linear representation of a non-Gaussian data set. Such a linear representation seems to be able to capture the essential structure of a laser beam profile. After assembling image data of a laser spot, we propose a new analytical approach to extract laser beam mode components based on the independent component analysis technique. For noise reduction and laser spot area location, wavelet thresholding, Canny edge detection, and the Hough transform are also used in this method before extracting mode components. Finally, the experimental results show that our approach can separate the principal mode components in a real laser beam efficiently.

© 2005 Optical Society of America

OCIS Codes
(070.6020) Fourier optics and signal processing : Continuous optical signal processing
(140.3300) Lasers and laser optics : Laser beam shaping
(230.2090) Optical devices : Electro-optical devices

History
Original Manuscript: August 16, 2004
Revised Manuscript: March 16, 2005
Manuscript Accepted: March 28, 2005
Published: June 20, 2005

Citation
Hai-Tao Fang and De-Shuang Huang, "Extracting mode components in laser intensity distribution by independent component analysis," Appl. Opt. 44, 3646-3653 (2005)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-44-18-3646


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References

  1. A. B. Katrich, “Laser beam shape invariance parameters,” in Fourth International Workshop on Laser and Fiber-Optical Networks Modeling (IEEE, New York, 2002), pp. 249–251.
  2. Th. Graf, J.E. Balmer, “Laser beam quality, entropy and the limits of beam shaping,” Opt. Commun. 131, 77–83 (1996). [CrossRef]
  3. C. B. Roundy, “Laser beam quality characterization,” presented at the Conference on Lasers and Electro-Optics Lasers and Electro-Optics Applications (CLEO LEAP), Anaheim, Calif., 6 June 1996.
  4. C. B. Roundy, “Electronic beam diagnostics evaluate laser performance,” Laser Focus World (May1996), pp. 119–125.
  5. C. B. Roundy, “Practical applications of laser beam profiling,” Lasers Optronics (April1996), pp. 21–26.
  6. J. M. Fletcher, J. M. Darchuk, “Standardizing the measurement of spatial characteristics of optical beams,” in Laser Beam Radiometry, Proc. SPIE 888, 60–64 (1988). [CrossRef]
  7. H. Q. Shangguan, L. W. Casperon, “Estimation of scattered light on the surface of unclad optical fiber tips: a new approach,” Opt. Commun. 152, 307–312 (1998). [CrossRef]
  8. S. U. Pandey, “Measurement of two particle resolution in silicon drift detectors,” IEEE Trans. Nucl. Sci. 45(3), 315–320 (1998). [CrossRef]
  9. A. Hyvarinen, E. Oja, “Independent component analysis: algorithms and applications,” Neural Networks 13, 411–430 (2000). [CrossRef] [PubMed]
  10. Y. Cheung, L. Xu, “Independent component ordering in ICA time series analysis,” Neurocomputing 41, 145–152 (2001). [CrossRef]
  11. T. Yamaguchi, K. Itoh, “An algebraic solution to independent component analysis,” Opt. Commun. 178, 59–64 (2000). [CrossRef]
  12. A. J. Bell, T.J. Sejnowski, “An information-maximization approach to blind separation and blind deconvolution,” Neural Comput. 7, 1129–1159 (1995). [CrossRef] [PubMed]
  13. S. Amari, A. Cichocki, H. Yang, “A new learning algorithm for blind signal separation,” Adv. Neural Inform. Proces. Syst. 8, 757–763 (1996).
  14. S. Mallat, “A theory for multi-resolution signal decomposition: the wavelet representation,” IEEE Trans. Pattern Anal. Mach. Intel. 11, 674–693 (1989). [CrossRef]
  15. I. Daubechies, Ten Lectures on Wavelets, Vol. 61 of CBMS-NSF Regional Conference Series in Applied Mathematics (Society for Industrial and Applied Mathematics, Philadelphia, 1992). [CrossRef]
  16. H. K. Yuen, “Comparative study of Hough transform methods for circle finding,” Image Vision Comput. 8(1), 71–77 (1990). [CrossRef]
  17. D. J. Kerbyson, T. J. Athertson, “Circle detection using Hough transform filters,” in Proceedings of the Fifth International Conference on Image. Processing and its Applications (IEE, London, 1995). [CrossRef]
  18. J. Canny, “A computational approach to edge detection,” IEEE Trans. Pattern Anal. Mach. Intell. 8, 679–698 (1986). [CrossRef] [PubMed]
  19. M. Born, E. Wolf, Principles of Optics (Pergamon, London, 1987).
  20. D. L. Donoho, “Denoising by soft-thresholding,” IEEE Trans. Inf. Theory 41, 613–627 (1995). [CrossRef]

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