Multiscale analysis of the intensity fluctuation in a time series of dynamic speckle patterns

Applied Optics

Volumn 46, Issue 11, 2007, Pages 1979-1985

  Federico, Alejandro ^a   Kaufmann, Guillermo H ^b,c  

^a INSTITUTO NACIONAL DE TECNOLOGÍA INDUSTRIAL   (Argentina)

^b INSTITUTO DE FÍSICA ROSARIO   (Argentina)

^c UNIVERSIDAD NACIONAL DE ROSARIO   (Argentina)

Author keywords

[No Author keywords available]

Indexed keywords

PATTERN RECOGNITION; SPECKLE; TIME SERIES ANALYSIS;

INTENSITY FLUCTUATION; PAINT-DRYING PROCESSES;

WAVELET TRANSFORMS;

EID: 34248211754     PISSN: 1559128X     EISSN: 15394522     Source Type: Journal    
DOI: 10.1364/AO.46.001979     Document Type: Review

References (19)

1. Y. Aizu and T. Asakura, "Biospeckle," in Trends in Optics, A. Consortini, ed. (Academic, 1996), Chap. 2.
2. A. Oulamara, G. Tribillon, and J. Dovernoy, "Biological activity measurements on botanical specimen surfaces using a temporal decorrelation effect of laser speckle," J. Mod. Opt. 36, 165-179 (1989).
3. M. F. Limia, A. M. Nuñez, H. Rabal, and M. Trivi, "Wavelet transform analysis of dynamic speckle patterns texture," Appl. Opt. 41, 6745-6750 (2002).
4. M. Pajuelo, G. Baldwin, H. Rabal, N. Cap, R. Arizaga, and M. Trivi, "Biospeckle assessment of bruising in fruits," Opt. Lasers Eng. 40, 13-24 (2003).
5. H. Rabal, R. Arizaga, N. L. Cap, E. Grumel, and M. Trivi, "Numerical model for dynamic speckle: an approach using the movement of the scatterers," J. Opt. A 5, 5381-5385 (2003).
6. B. Ruiz, N. Cap, and H. Rabal, "Local correlation in dynamic speckle," Opt. Commun. 245, 103-111 (2005).
7. G. J. Tearney and B. E. Bouma, "Atherosclerotic plaque characterization by spatial and temporal speckle pattern analysis," Opt. Lett. 27, 533-535 (2002).
8. P. Yu, I. Peng, M. Mustata, J. J. Turek, M. R. Melloch, and D. D. Nolte, "Time-dependent speckle in holographic optical coherence imaging and the health of tumor tissue," Opt. Lett. 29, 68-70 (2004).
9. G. H. Sendra, R. Arizaga, H. Rabal, and M. Trivi, "Decomposition of biospeckle images in temporary spectral bands," Opt. Lett. 30, 1641-1643 (2005).
10. L. T. Passoni, H. Rabal, and C. M. Arizmendi, "Characterizing dynamic speckle time data set with the Hurst coefficient concept," Fractals 12, 319-328 (2004).
11. G. M. Zaslavsky, "Chaos, fractional kinetics, and anomalous transport," Phys. Rep. 371, 461-580 (2002).
12. P. Abry, P. Flandrin, M. Taqqu, and D. Veitch, "Wavelets for the analysis, estimation and synthesis of scaling data," in Self-Similar Network Traffic and Performance Evaluation, K. Park and W. Willinger, eds. (Wiley, 2000), pp. 39-87.
13. H. Rabal, N. Cap, M. Trivi, R. Arizaga, A. Federico, G. E. Galizzi, and G. H. Kaufmann, "Speckle activity images based on the spatial variance of the phase," Appl. Opt. 45, 8733-8738 (2006).
14. A. Federico and G. H. Kaufmann, "Evaluation of dynamic speckle activity using the empirical mode decomposition method," Opt. Commun. 267, 287-294 (2006).
15. E. Bacry, J. F. Muzy, and A. Arnéodo, "Singularity spectrum of fractal signals from wavelet analysis: exact results," J. Stat. Phys. 70, 635-675 (1993).
16. S. Jaffard, "Multifractal formalism for functions part I: results valid for all functions," SIAM J. Math. Anal. 28, 944-970 (1997).
17. S. Jaffard, "Multifractal formalism for functions part II: self-similar functions," SIAM J. Math. Anal. 28, 971-998 (1997).
18. A. Federico and G. H. Kaufmann, "Multifractals and dynamic speckle," Proc. SPIE 6341, 63412J (2006).
19. J. Theiler, S. Eubank, A. Longtin, B. Galdrikian, and J. D. Farmer, "Testing for nonlinearity in time series: the method of surrogate data," Physica D 58, 77-94 (1992).