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Applied Optics

Applied Optics


  • Vol. 43, Iss. 28 — Oct. 1, 2004
  • pp: 5356–5363

Bayesian neural-networks-based evaluation of binary speckle data

Udo V. Toussaint, Silvio Gori, and Volker Dose  »View Author Affiliations

Applied Optics, Vol. 43, Issue 28, pp. 5356-5363 (2004)

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We present a new method using Bayesian probability theory and neural networks for the evaluation of speckle interference patterns for an automated analysis of deformation and erosion measurements. The method is applied to the fringe pattern reconstruction of speckle measurements with a Twyman-Green interferometer. Given a binary speckle image, the method returns the fringe pattern without noise, thus removing the need for smoothing and allowing a straightforward unwrapping procedure and determination of the surface shape. Because no parameters have to be adjusted, the method is especially suited for continuous and automated monitoring of surface changes.

© 2004 Optical Society of America

OCIS Codes
(100.2650) Image processing : Fringe analysis
(100.5010) Image processing : Pattern recognition
(120.6160) Instrumentation, measurement, and metrology : Speckle interferometry

Original Manuscript: February 5, 2004
Revised Manuscript: June 25, 2004
Published: October 1, 2004

Udo V. Toussaint, Silvio Gori, and Volker Dose, "Bayesian neural-networks-based evaluation of binary speckle data," Appl. Opt. 43, 5356-5363 (2004)

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  1. G. Janeschitz, “Plasma-wall interaction issues in ITER,” J. Nucl. Mater. 290–293, 1–11 (2001). [CrossRef]
  2. R. A. Zuhr, J. Roth, W. Eckstein, U. V. Toussaint, J. Luthin, “Implantation, erosion, and retention of tungsten in carbon,” J. Nucl. Mater. 290–293, 162–165 (2001). [CrossRef]
  3. E. Gauthier, G. Roupillard, “Speckle interferometry diagnostic for erosion/redeposition measurements in tokamaks,” J. Nucl. Mater. 313–316, 701–705 (2003). [CrossRef]
  4. R. M. Goldstein, H. A. Zebker, C. L. Werner, “Satellite radar interferometry: two-dimensional phase unwrapping,” Radio Sci. 23, 713–720 (1988). [CrossRef]
  5. J. M. Huntley, “Noise-immune phase unwrapping algorithm,” Appl. Opt. 28, 3268–3270 (1989). [CrossRef] [PubMed]
  6. J. R. Buckland, J. M. Huntley, S. R. E. Turner, “Unwrapping noisy phase maps by use of a minimum-cost-matching algorithm,” Appl. Opt. 34, 5100–5108 (1995). [CrossRef] [PubMed]
  7. J. M. Huntley, “Automated fringe pattern analysis in experimental mechanics: a review,” J. Strain Anal. 33, 105–125 (1998). [CrossRef]
  8. R. Seara, A. A. Goncalves, P. B. Uliana, “Filtering algorithm for noise reduction in phase images with 2π phase jumps,” Appl. Opt. 37, 2046–2050 (1998). [CrossRef]
  9. D. C. Ghiglia, G. A. Mastin, L. A. Romero, “Cellular-automata method for phase unwrapping,” J. Opt. Soc. Am. A 4, 267–280 (1987). [CrossRef]
  10. D. J. Tipper, D. R. Burton, M. J. Lalor, “A neural network approach to the phase unwrapping problem in fringe analysis,” Nondestr. Test. Eval. 12, 391–400 (1996). [CrossRef]
  11. P. G. Charette, I. W. Hunter, “Robust phase-unwrapping method for phase images with high noise content,” Appl. Opt. 35, 3506–3513 (1996). [CrossRef] [PubMed]
  12. M. A. Herraez, M. A. Gdeisat, D. R. Burton, M. J. Lalor, “Robust, fast, and effective two-dimensional automatic phase unwrapping algorithm based on image decomposition,” Appl. Opt. 41, 7445–7455 (2002). [CrossRef] [PubMed]
  13. J. Arines, “Least-squares model estimation of wrapped phases: application to phase unwrapping,” Appl. Opt. 42, 3373–3378 (2003). [CrossRef] [PubMed]
  14. O. Marklund, “Noise-insensitive two-dimensional phase unwrapping method,” J. Opt. Soc. Am. A 15, 42–60 (1998). [CrossRef]
  15. X. Y. He, X. Kang, C. J. Tay, C. Quan, H. M. Shang, “Proposed algorithm for phase unwrapping,” Appl. Opt. 41, 7422–7428 (2002). [CrossRef] [PubMed]
  16. B. V. Dorrio, J. L. Fernandez, “Phase-evaluation methods in whole-field optical measurement techniques,” Meas. Sci. Technol. 10, R33–R55 (1999). [CrossRef]
  17. E. Berger, W. von der Linden, V. Dose, M. Ruprecht, A. Koch, “Approach for the evaluation of speckle deformation measurements by application of the wavelet transformation,” Appl. Opt. 36, 7455–7460 (1997). [CrossRef]
  18. C. M. Bishop, Neural Networks for Pattern Recognition (Oxford U. Press, Oxford, UK, 1995).
  19. A. R. Barron, “Universal approximation bounds for superposition of a sigmoidal function,” IEEE Trans. Inf. Theory 39, 930–945 (1993). [CrossRef]
  20. D. Sivia, Data Analysis: A Bayesian Tutorial (Oxford U. Press, Oxford, UK, 1996).
  21. E. T. Jaynes, “Prior probabilities,” in Papers on Probability, Statistics and Statistical Physics, R. Rosenkrantz, ed. (Reidel, Dordrecht, The Netherlands, 1983).
  22. V. Dose, “Hyperplane priors,” in Bayesian Inference and Maximum Entropy Methods in Science and Engineering: 23rd International Workshop, C. J. Williams, ed. (American Institute of Physics, Melville, N.Y., 2003), pp. 350–357.
  23. B. Buck, V. A. Macaulay, Maximum Entropy in Action (Oxford U. Press, Oxford, UK, 1991).
  24. U. V. Toussaint, S. Gori, V. Dose, “A Bayesian neural network,” Neural Networks, submitted for publication.
  25. R. M. Neal, “Bayesian learning for neural networks,” in Lecture Notes in Statistics, P. Bickel, P. Diggle, S. Fienberg, U. Gather, I. Olkin, S. Zeger, eds. (Springer, New York, 1996), Vol. 118. [CrossRef]
  26. E. Berger, W. von der Linden, V. Dose, M. Jakobi, A. W. Koch, “Reconstruction of surfaces from phase-shifting speckle interferometry,” Appl. Opt. 38, 4997–5003 (1999). [CrossRef]
  27. Optimization routine nag_nlp_sol, mark18 from Numerical Algorithms Group Ltd., Oxford, OX2 8DR, UK, http://www.nag.co.uk .
  28. H. H. Thodberg, “A review of Bayesian neural networks with an application to near infrared spectroscopy,” IEEE Trans. Neural Networks 7, 56–72 (1995). [CrossRef]
  29. D. Kerr, G. H. Kaufmann, G. E. Galizzi, “Unwrapping of interferometric phase-fringe maps by discrete cosine transform,” Appl. Opt. 35, 810–816 (1996). [CrossRef] [PubMed]
  30. G. H. Kaufmann, G. E. Galizzi, P. D. Ruiz, “Evaluation of a preconditioned conjugate-gradient algorithm for weighted least-squares unwrapping of digital speckle-pattern interferometry phase maps,” Appl. Opt. 37, 3076–3084 (1998). [CrossRef]
  31. T. R. Crimmins, “Geometric filter for speckle reduction,” Appl. Opt. 24, 1438–1443 (1985). [CrossRef] [PubMed]
  32. T. R. Crimmins, “Geometric filter for reducing speckle,” Opt. Eng. 25, 651–654 (1986). [CrossRef]
  33. J. S. Lee, I. Jurkevich, “Speckle filtering of synthetic aperture radar images: a review,” Remote Sens. Rev. 8, 313–340 (1994). [CrossRef]
  34. J. S. Lee, “A simple speckle smoothing algorithm for synthetic aperture radar images,” IEEE Trans. Syst. Man. Cybern. SMC-13, 85–89 (1983). [CrossRef]
  35. D. T. Kuan, A. A. Sawchuk, T. C. Strand, P. Chavel, “Adaptive restoration of images with speckle,” IEEE Trans. Acoust. Speech Signal Process. 35, 373–383 (1987). [CrossRef]
  36. A. Lopes, R. Touzi, E. Nezry, “Adaptive speckle filters and scene heterogeneity,” IEEE Trans. Geosci. Remote Sens. 28, 992–1000 (1990). [CrossRef]
  37. J. S. Lee, “Digital image noise smoothing and the sigma filter,” Comput. Vision Graph. Image Process. 24, 255–269 (1983). [CrossRef]

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