OSA's Digital Library

Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 50, Iss. 21 — Jul. 20, 2011
  • pp: 3973–3986

Efficient fringe image enhancement based on dual-tree complex wavelet transform

Tai-Chiu Hsung, Daniel Pak-Kong Lun, and William W.L. Ng  »View Author Affiliations


Applied Optics, Vol. 50, Issue 21, pp. 3973-3986 (2011)
http://dx.doi.org/10.1364/AO.50.003973


View Full Text Article

Enhanced HTML    Acrobat PDF (1529 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

In optical phase shift profilometry (PSP), parallel fringe patterns are projected onto an object and the deformed fringes are captured using a digital camera. It is of particular interest in real time three- dimensional (3D) modeling applications because it enables 3D reconstruction using just a few image captures. When using this approach in a real life environment, however, the noise in the captured images can greatly affect the quality of the reconstructed 3D model. In this paper, a new image enhancement algorithm based on the oriented two-dimenional dual-tree complex wavelet transform (DT-CWT) is proposed for denoising the captured fringe images. The proposed algorithm makes use of the special analytic property of DT-CWT to obtain a sparse representation of the fringe image. Based on the sparse representation, a new iterative regularization procedure is applied for enhancing the noisy fringe image. The new approach introduces an additional preprocessing step to improve the initial guess of the iterative algorithm. Compared with the traditional image enhancement techniques, the proposed algorithm achieves a further improvement of 7.2 dB on average in the signal-to-noise ratio (SNR). When applying the proposed algorithm to optical PSP, the new approach enables the reconstruction of 3D models with improved accuracy from 6 to 20 dB in the SNR over the traditional approaches if the fringe images are noisy.

© 2011 Optical Society of America

OCIS Codes
(100.2650) Image processing : Fringe analysis
(100.5070) Image processing : Phase retrieval
(100.7410) Image processing : Wavelets
(110.4280) Imaging systems : Noise in imaging systems
(100.5088) Image processing : Phase unwrapping

ToC Category:
Image Processing

History
Original Manuscript: September 7, 2010
Revised Manuscript: April 26, 2011
Manuscript Accepted: May 24, 2011
Published: July 14, 2011

Citation
Tai-Chiu Hsung, Daniel Pak-Kong Lun, and William W.L. Ng, "Efficient fringe image enhancement based on dual-tree complex wavelet transform," Appl. Opt. 50, 3973-3986 (2011)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-50-21-3973


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. S. Zhang and S. T. Yau, “High-speed three-dimensional shape measurement system using a modified two-plus-one phase-shifting algorithm,” Opt. Eng. 46, 113603 (2007). [CrossRef]
  2. T. W. Hui and G. K. H. Pang, “3-D measurement of solder paste using two-step phase shift profilometry,” IEEE Trans. Electron. Packag. Manufact. 31, 306–315 (2008). [CrossRef]
  3. X. Su and W. Chen, “Fourier transform profilometry: A review,” Opt. Lasers Eng. 35, 263–284 (2001). [CrossRef]
  4. M. Takeda and K. Mutoh, “Fourier transform profilometry for the automatic measurement of 3-D object shapes,” Appl. Opt. 22, 3977–3982 (1983). [CrossRef] [PubMed]
  5. J. Zhong and J. Weng, “Spatial carrier-fringe pattern analysis by means of wavelet transform: Wavelet transform profilometry,” Appl. Opt. 43, 4993–4998 (2004). [CrossRef] [PubMed]
  6. J. Zhong and J. Weng, “Phase retrieval of optical fringe patterns from the ridge of a wavelet transform,” Opt. Lett. 30, 2560–2562 (2005). [CrossRef] [PubMed]
  7. M. A. Gdeisat, D. R. Burton, and M. J. Lalor, “Spatial carrier fringe pattern demodulation by use of a two-dimensional continuous wavelet transform,” Appl. Opt. 45, 8722–8732 (2006). [CrossRef] [PubMed]
  8. S. Li, X. Su, and W. J. Chen, “Spatial carrier fringe pattern phase demodulation by use of a two-dimensional real wavelet,” Appl. Opt. 48, 6893–6906 (2009). [CrossRef] [PubMed]
  9. D. C. Ghiglia and M. D. Pritt, Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software (Wiley, 1998).
  10. J. Bioucas-Dias and G. Valadao, “Phase unwrapping via graph cuts,” IEEE Trans. Image Process. 16, 698–709 (2007). [CrossRef] [PubMed]
  11. J. S. Lee, K. P. Papathanassiou, T. L. Ainsworth, M. R. Grunes, and A. Reigber, “A new technique for noise filtering of SAR interferometric phase images,” IEEE Trans. Geosci. Remote Sens. 36, 1456–1465 (1998). [CrossRef]
  12. C. Lopez-Martinez and X. Fabregas, “Modeling and reduction of SAR interferometric phase noise in the wavelet domain,” IEEE Trans. Geosci. Remote Sens. 40, 2553–2566 (2002). [CrossRef]
  13. J. Bioucas-Dias, V. Katkovnik, J. Astola, and K. Egiazarian, “Absolute phase estimation: Adaptive local denoising and global unwrapping,” Appl. Opt. 47, 5358–5369 (2008). [CrossRef] [PubMed]
  14. V. Katkovnik, J. Astola, and K. Egiazarian, “Phase local approximation (PhaseLa) technique for phase unwrap from noisy data,” IEEE Trans. Image Process. 17, 833–846 (2008). [CrossRef] [PubMed]
  15. K. Qian, “Windowed Fourier transform for fringe pattern analysis,” Appl. Opt. 43, 2695–2702 (2004). [CrossRef]
  16. K. Qian, “Windowed Fourier transform for fringe pattern analysis: Addendum,” Appl. Opt. 43, 3472–3473 (2004). [CrossRef]
  17. K. Qian, “Windowed Fourier transform for fringe pattern analysis: Principles, applications and implementations,” Opt. Lasers Eng. 45, 304–317 (2007). [CrossRef]
  18. K. Qian, H. N. Le Tran, F. Lin, and H. S. Seah, “Comparative analysis on some filters for wrapped phase maps,” Appl. Opt. 46, 7412–7418 (2007). [CrossRef]
  19. L. Huang, Q. Kemao, B. Pan, and A. K. Asundi, “Comparison of Fourier transform, windowed Fourier transform, and wavelet transform methods for phase extraction from a single fringe pattern in fringe projection profilometry,” Opt. Lasers Eng. 48, 141–148 (2010). [CrossRef]
  20. I. Daubechies, M. Defrise, and C. D. Mol, “An iterative thresholding algorithm for linear inverse problems with a sparsity constraint,” Commun. Pure Appl. Math. 57, pp. 1413–1457(2004). [CrossRef]
  21. M. Elad, “Why simple shrinkage is still relevant for redundant representations?” IEEE Trans. Inf. Theory 52, 5559–5569(2006). [CrossRef]
  22. M. Elad, B. Matalon, and M. Zibulevsky, “Image denoising with shrinkage and redundant representations,” 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2006), Vol.  2, pp. 1924–1931.
  23. J. M. Bioucas-Dias and M. A. T. Figueiredo, “A new TwIST: Two-step iterative shrinkage/thresholding algorithms for image restoration,” IEEE Trans. Image Process. 16, 2992–3004(2007). [CrossRef] [PubMed]
  24. A. M. Bruckstein, D. L. Donoho, and M. Elad, “From sparse solutions of systems of equations to sparse modeling of signals and images,” SIAM Rev. 51, 34–81 (2009). [CrossRef]
  25. I. W. Selesnick, R. G. Baraniuk, and N. G. Kingsbury, “The dual-tree complex wavelet transform,” IEEE Signal Process. 123–151 (2005). [CrossRef]
  26. H. Shi, B. Hu, and J. Q. Zhang, “A novel scheme for the design of approximate Hilbert transform pairs of orthonormal wavelet bases,” IEEE Trans. Signal Process. 56, 2289–2297(2008). [CrossRef]
  27. D. L. Donoho and I. M. Johnstone, “Adapting to unknown smoothness via wavelet shrinkage,” J. Am. Stat. Assoc. 90, 1200–1224 (1995). [CrossRef]
  28. S. G. Mallat, A Wavelet Tour of Signal Processing (Academic, 1999).
  29. P. Duhamel and H. Hollmann, “‘Split radix’ FFT algorithm,” Electron. Lett. 20, 14–16 (1984). [CrossRef]
  30. S. G. Johnson and M. Frigo, “A modified split-radix FFT with fewer arithmetic operations,” IEEE Trans. Signal Process. 55, 111–119 (2007). [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