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Applied Optics

Applied Optics


  • Vol. 37, Iss. 34 — Dec. 1, 1998
  • pp: 8153–8153

Micro-displacement by Means of Optoelectronic Nonlinear Joint Transform Correlation of Speckle Pattern

J. Guerrero-Bermútdez, C. Torres, O. Gualdron, Y. Torres, and L. Salazar  »View Author Affiliations

Applied Optics, Vol. 37, Issue 34, pp. 8153-8153 (1998)

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Two objective speckle patterns are obtained—one before and one after the object has been moved—and are placed in the input plane of an optoelectronic nonlinear joint transform correlator.Nonlinear transformation of the joint power spectrum permits a sharper correlation peak and a high signal-to-noise ratio. The autocorrelation peak coordinates of the first pattern are set as a reference for measuring displacements of the cross-correlation peak, and also, the calibration of the measurement system is performed.It is well known that speckle can be regarded as a random spatial carrier in which information on the shape and position of the diffusing surface is encoded. The correlation of speckle patterns is highly appropriate for measuring displacements of tens of micrometers.1,2 In this work, an alternative technique based on the correlation between two speckle patterns by means of a digital bipolar joint transform correlator3 is presented. Initially the technique is described and then experimental results are shown.

© 1998 Optical Society of America

J. Guerrero-Bermútdez, C. Torres, O. Gualdron, Y. Torres, and L. Salazar, "Micro-displacement by Means of Optoelectronic Nonlinear Joint Transform Correlation of Speckle Pattern," Appl. Opt. 37, 8153-8153 (1998)

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  1. C. Gorecki, G. Tribillon, “Speckle displacement analysis by phase correlation using a SLM-based processor,” Journal of Modern Optics 40(6). 973–978 (1993). [CrossRef]
  2. A. Oulamara et al., “Subpixel speckle displacement measurement using a digital processing technique.” Journal of Modern Optics 35(7), 1201–1211 (1988). [CrossRef]
  3. B. Javidi, Nonlinear Joint Transform Correlators in Real Time Optical Information Processing (Academic Press Inc., San Diego, CA, 1994), pp. 115–183.
  4. B. Javidi, D. Painchaud. “Distortion–invariant pattern recognition with Fourier-plane nonlinear filters,” Appl. Opt. 35(2), 318–331 (1996). [CrossRef] [PubMed]

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