OSA's Digital Library

Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 19, Iss. 19 — Sep. 12, 2011
  • pp: 18207–18215

Adaptive noise reduction method for DSPI fringes based on bi-dimensional ensemble empirical mode decomposition

Yi Zhou and Hongguang Li  »View Author Affiliations


Optics Express, Vol. 19, Issue 19, pp. 18207-18215 (2011)
http://dx.doi.org/10.1364/OE.19.018207


View Full Text Article

Enhanced HTML    Acrobat PDF (1275 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

Digital speckle pattern interferometry (DSPI) fringes contain low spatial information degraded with speckle noise and background intensity. The denoising technique proposed recently based on bi-dimensional empirical mode decomposition (BEMD) could implement noise reduction adaptively. However, the major drawback of BEMD, called mode mixing, has affected its practical application. With noise-assisted data analysis (NADA) method, bi-dimensional ensemble empirical mode decomposition (BEEMD) was proposed, which has solved the problem of mode mixing. The denoising approach based on BEEMD will be presented, compared with other classic denoising methods and evaluated both qualitatively and quantitatively using computer-simulated and experimental DSPI fringes.

© 2011 OSA

OCIS Codes
(100.2000) Image processing : Digital image processing
(100.2650) Image processing : Fringe analysis
(100.2980) Image processing : Image enhancement
(120.6150) Instrumentation, measurement, and metrology : Speckle imaging
(120.6160) Instrumentation, measurement, and metrology : Speckle interferometry

ToC Category:
Image Processing

History
Original Manuscript: August 7, 2011
Revised Manuscript: August 8, 2011
Manuscript Accepted: August 8, 2011
Published: September 1, 2011

Citation
Yi Zhou and Hongguang Li, "Adaptive noise reduction method for DSPI fringes based on bi-dimensional ensemble empirical mode decomposition," Opt. Express 19, 18207-18215 (2011)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-19-19-18207


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. M. B. Bernini, A. Federico, and G. H. Kaufmann, “Noise reduction in digital speckle pattern interferometry using bidimensional empirical mode decomposition,” Appl. Opt.47(14), 2592–2598 (2008). [CrossRef] [PubMed]
  2. Z. Wu and N. E. Huang, “Ensemble empirical mode decomposition: a noise assisted data analysis method,” Adv. Adapt. Data Anal.1(01), 1–41 (2009). [CrossRef]
  3. Z. Wu, N. E. Huang, and X. Chen, “The multi-dimensional ensemble empirical mode decomposition,” Adv. Adapt. Data Anal.1(03), 339–372 (2009). [CrossRef]
  4. A. Federico and G. H. Kaufmann, “Phase retrieval in digital speckle pattern interferometry by application of two-dimensional active contours called snakes,” Appl. Opt.45(9), 1909–1916 (2006). [CrossRef] [PubMed]
  5. R. Kumar, D. P. Jena, and C. Shakher, “Application of wavelet transform and image morphology in processing vibration speckle interferogram for automatic analysis,” Proc. SPIE8082, 80821Y, 80821Y-5 (2011). [CrossRef]
  6. A. Federico and G. H. Kaufmann, “Comparative study of wavelet thresholding methods for denoising electronic speckle pattern interferometry fringes,” Opt. Eng.40(11), 2598–2604 (2001). [CrossRef]
  7. X. Zhou, H. Zhao, and T. Jiang, “Adaptive analysis of optical fringe patterns using ensemble empirical mode decomposition algorithm,” Opt. Lett.34(13), 2033–2035 (2009). [CrossRef] [PubMed]
  8. A. Federico and G. H. Kaufmann, “Local denoising of digital speckle pattern interferometry fringes by multiplicative correlation and weighted smoothing splines,” Appl. Opt.44(14), 2728–2735 (2005). [CrossRef] [PubMed]
  9. P. D. Ruiz and G. H. Kaufmann, “Evaluation of a scale-space filter for speckle noise reduction in electronic speckle pattern interferometry,” Opt. Eng.37(8), 2395 (1998). [CrossRef]
  10. Z. Wang and A. C. Bovik, “A universal image quality index,” IEEE Signal Process. Lett.9(3), 81–84 (2002). [CrossRef]
  11. A. W. Leissa, “The free vibration of rectangular plates,” J. Sound Vibrat.31(3), 257–293 (1973). [CrossRef]
  12. C. Loizou, C. Christodoulou, C. S. Pattichis, R. Istepanian, M. Pantziaris, and A. Nicolaides, “Speckle reduction in ultrasound images of atherosclerotic carotid plaque,” Proc. IEEE 14th Intl. Conf. Digital Signal Process, 525–528 (2002).
  13. T. R. Crimmins, “Geometric filter for speckle reduction,” Appl. Opt.24(10), 1438–1443 (1985). [CrossRef] [PubMed]
  14. C. Shakher, R. Kumar, S. K. Singh, and S. A. Kazmi, “Application of wavelet filtering for vibration analysis using digital speckle pattern interferometry,” Opt. Eng.41(1), 176 (2002). [CrossRef]
  15. R. Kumar, I. P. Singh, and C. Shakher, “Measurement of out-of-plane static and dynamic deformations by processing digital speckle pattern interferometry fringes using wavelet transform,” Opt. Lasers Eng.41(1), 81–93 (2004). [CrossRef]
  16. R. Kumar, “Wavelet filtering applied to time-average digital speckle pattern interferometry fringes,” Opt. Laser Technol.33(8), 567–571 (2001). [CrossRef]
  17. K. Creath, “Temporal phase method,” in Interferogram Analysis, D. Robinson, and G. Reid, eds. (Institute of Physics, 1993), pp. 94–140.
  18. Y. Lei, Z. He, and Y. Zi, “Application of the EEMD method to rotor fault diagnosis of rotating machinery,” Mech. Syst. Signal Process.23(4), 1327–1338 (2009). [CrossRef]

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