Abstract

The profile measurement system is widely used in industrial quality control, and phase unwrapping (PU) is a key technique. An algorithm-driven PU is often used to reduce the impact of noise-induced residues to retrieve the most reliable solution. However, measuring speed is lowered due to the searching of optimal integration paths or correcting of phase gradients. From the viewpoint of the rapidity of the system, this paper characterizes the noise-induced residues, and it proposes a clustering-driven residue filter based on a set of directional windows. The proposed procedure makes the wrapped phases included in the filtering window have more similar values, and it groups the correct and noisy phases into individual clusters along the local fringe direction adaptively. It is effective for the tightly packed fringes, and it converts the algorithm-driven PU to the residue-filtering-driven one. This improves the operating speed of the 3D reconstruction significantly. The tests performed on simulated and real projected fringes confirm the validity of our approach.

© 2011 Optical Society of America

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    [CrossRef]
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    [CrossRef]
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  23. cmin is the cluster in which the number of members is smallest.
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    [CrossRef]
  25. cmax is the cluster in which the number of members is biggest.
  26. D. C. Ghiglia and M. D. Pritt, Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software (Wiley, 1998).

2010 (2)

S. S. Gorthi and P. Rastogi, “Fringe projection techniques: whither we are?” Opt. Lasers Eng. 48, 133–140 (2010).
[CrossRef]

J. Jiang, J. Cheng, and B. Luong, “Unsupervised-clustering-driven noise-residue filter for phase images,” Appl. Opt. 49, 2143–2150 (2010).
[CrossRef]

2009 (1)

V. Chandola, A. Banerjee, and V. Kumar, “Anomaly detection: a survey,” ACM Comput. Surv. 41, 1–58 (2009).
[CrossRef]

2008 (1)

2007 (2)

2005 (1)

G. Fornaro, A. Pauciullo, and E. Sansosti, “Phase difference-based multichannel phase unwrapping,” IEEE Trans. Image Process. 14, 960–972 (2005).
[CrossRef]

2004 (1)

2003 (1)

2000 (4)

F. Chen, G. M. Brown, and M. Song, “Overview of three-dimensional shape measurement using optical methods,” Opt. Eng. 39, 10–22 (2000).
[CrossRef]

G. Nico, G. Palubinskas, and M. Datcu, “Bayesian approaches to phase unwrapping: theoretical study,” IEEE Trans. Signal Process. 48, 2545–2556 (2000).
[CrossRef]

L. An, Q. S. Xiang, and S. Chavez, “A fast implementation of the minimum spanning tree method for phase unwrapping,” IEEE Trans. Med. Imaging 19, 805–808 (2000).
[CrossRef]

G. Nico, “Noise-residue filtering of interferometric phase images,” J. Opt. Soc. Am. A. 17, 1962–1974 (2000).
[CrossRef]

1998 (4)

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 Sensing 36, 1173 (1998).
[CrossRef]

J. M. N. Leitão and M. A. T. Figueiredo, “Absolute phase image reconstruction: a stochastic nonlinear filtering approach,” IEEE Trans. Image Process. 7, 868–882 (1998).
[CrossRef]

M. Costantini, “A novel phase unwrapping method based on network programming,” IEEE Trans. Geosci. Remote Sensing 36, 813–821 (1998).
[CrossRef]

H. A. Zebker and Y. P. Lu, “Phase unwrapping algorithms for radar interferometry: residue-cut, least-squares, and synthesis algorithms,” J. Opt. Soc. Am. A 15, 586–598 (1998).
[CrossRef]

1997 (1)

A. Capanni, L. Pezzati, D. Bertani, M. Cetica, and F. Francini, “Phase-shifting speckle interferometry: a noise reduction filter for phase unwrapping,” Opt. Eng. 36, 2466–2472 (1997).
[CrossRef]

1996 (2)

Z. P. Liang, “A model-based method for phase unwrapping,” IEEE Trans. Med. Imaging 15, 893–897 (1996).
[CrossRef]

D. C. Ghiglia and L. A. Romero, “Minimum Lp-norm two-dimensional phase unwrapping,” J. Opt. Soc. Am. A 13, 1999–2013 (1996).
[CrossRef]

1982 (1)

Adam, N.

Ainsworth, T. L.

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 Sensing 36, 1173 (1998).
[CrossRef]

An, L.

L. An, Q. S. Xiang, and S. Chavez, “A fast implementation of the minimum spanning tree method for phase unwrapping,” IEEE Trans. Med. Imaging 19, 805–808 (2000).
[CrossRef]

Baldi, A.

Banerjee, A.

V. Chandola, A. Banerjee, and V. Kumar, “Anomaly detection: a survey,” ACM Comput. Surv. 41, 1–58 (2009).
[CrossRef]

Berkhin, P.

P. Berkhin, Survey of Clustering Data Mining Techniques (Springer, 2002).

Bertani, D.

A. Capanni, L. Pezzati, D. Bertani, M. Cetica, and F. Francini, “Phase-shifting speckle interferometry: a noise reduction filter for phase unwrapping,” Opt. Eng. 36, 2466–2472 (1997).
[CrossRef]

Brown, G. M.

F. Chen, G. M. Brown, and M. Song, “Overview of three-dimensional shape measurement using optical methods,” Opt. Eng. 39, 10–22 (2000).
[CrossRef]

Burton, D. R.

Capanni, A.

A. Capanni, L. Pezzati, D. Bertani, M. Cetica, and F. Francini, “Phase-shifting speckle interferometry: a noise reduction filter for phase unwrapping,” Opt. Eng. 36, 2466–2472 (1997).
[CrossRef]

Cetica, M.

A. Capanni, L. Pezzati, D. Bertani, M. Cetica, and F. Francini, “Phase-shifting speckle interferometry: a noise reduction filter for phase unwrapping,” Opt. Eng. 36, 2466–2472 (1997).
[CrossRef]

Chandola, V.

V. Chandola, A. Banerjee, and V. Kumar, “Anomaly detection: a survey,” ACM Comput. Surv. 41, 1–58 (2009).
[CrossRef]

Chavez, S.

L. An, Q. S. Xiang, and S. Chavez, “A fast implementation of the minimum spanning tree method for phase unwrapping,” IEEE Trans. Med. Imaging 19, 805–808 (2000).
[CrossRef]

Chen, F.

F. Chen, G. M. Brown, and M. Song, “Overview of three-dimensional shape measurement using optical methods,” Opt. Eng. 39, 10–22 (2000).
[CrossRef]

Cheng, J.

J. Jiang, J. Cheng, and B. Luong, “Unsupervised-clustering-driven noise-residue filter for phase images,” Appl. Opt. 49, 2143–2150 (2010).
[CrossRef]

J. Jiang and J. Cheng, “Noise-residue filtering based on unsupervised clustering for phase unwrapping,” in Proceedings of 5th International Symposium on Visual Computing, M.Z.Nashed, ed. (Springer, 2009), pp. 719–727.

Costantini, M.

M. Costantini, “A novel phase unwrapping method based on network programming,” IEEE Trans. Geosci. Remote Sensing 36, 813–821 (1998).
[CrossRef]

Datcu, M.

G. Nico, G. Palubinskas, and M. Datcu, “Bayesian approaches to phase unwrapping: theoretical study,” IEEE Trans. Signal Process. 48, 2545–2556 (2000).
[CrossRef]

Du, H.

Figueiredo, M. A. T.

J. M. N. Leitão and M. A. T. Figueiredo, “Absolute phase image reconstruction: a stochastic nonlinear filtering approach,” IEEE Trans. Image Process. 7, 868–882 (1998).
[CrossRef]

Fornaro, G.

G. Fornaro, A. Pauciullo, and E. Sansosti, “Phase difference-based multichannel phase unwrapping,” IEEE Trans. Image Process. 14, 960–972 (2005).
[CrossRef]

Francini, F.

A. Capanni, L. Pezzati, D. Bertani, M. Cetica, and F. Francini, “Phase-shifting speckle interferometry: a noise reduction filter for phase unwrapping,” Opt. Eng. 36, 2466–2472 (1997).
[CrossRef]

Gao, W.

Gdeisat, M. A.

Ghiglia, D. C.

D. C. Ghiglia and L. A. Romero, “Minimum Lp-norm two-dimensional phase unwrapping,” J. Opt. Soc. Am. A 13, 1999–2013 (1996).
[CrossRef]

D. C. Ghiglia and M. D. Pritt, Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software (Wiley, 1998).

Gorthi, S. S.

S. S. Gorthi and P. Rastogi, “Fringe projection techniques: whither we are?” Opt. Lasers Eng. 48, 133–140 (2010).
[CrossRef]

Grunes, M. R.

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 Sensing 36, 1173 (1998).
[CrossRef]

Hubig, M.

Itoh, K.

Jiang, J.

J. Jiang, J. Cheng, and B. Luong, “Unsupervised-clustering-driven noise-residue filter for phase images,” Appl. Opt. 49, 2143–2150 (2010).
[CrossRef]

J. Jiang and J. Cheng, “Noise-residue filtering based on unsupervised clustering for phase unwrapping,” in Proceedings of 5th International Symposium on Visual Computing, M.Z.Nashed, ed. (Springer, 2009), pp. 719–727.

Karout, S. A.

Kumar, V.

V. Chandola, A. Banerjee, and V. Kumar, “Anomaly detection: a survey,” ACM Comput. Surv. 41, 1–58 (2009).
[CrossRef]

Lalor, M. J.

Lee, J. S.

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 Sensing 36, 1173 (1998).
[CrossRef]

Leitão, J. M. N.

J. M. N. Leitão and M. A. T. Figueiredo, “Absolute phase image reconstruction: a stochastic nonlinear filtering approach,” IEEE Trans. Image Process. 7, 868–882 (1998).
[CrossRef]

Liang, Z. P.

Z. P. Liang, “A model-based method for phase unwrapping,” IEEE Trans. Med. Imaging 15, 893–897 (1996).
[CrossRef]

Lu, Y. P.

Luong, B.

Nico, G.

G. Nico, G. Palubinskas, and M. Datcu, “Bayesian approaches to phase unwrapping: theoretical study,” IEEE Trans. Signal Process. 48, 2545–2556 (2000).
[CrossRef]

G. Nico, “Noise-residue filtering of interferometric phase images,” J. Opt. Soc. Am. A. 17, 1962–1974 (2000).
[CrossRef]

Palubinskas, G.

G. Nico, G. Palubinskas, and M. Datcu, “Bayesian approaches to phase unwrapping: theoretical study,” IEEE Trans. Signal Process. 48, 2545–2556 (2000).
[CrossRef]

Papathanassiou, K. P.

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 Sensing 36, 1173 (1998).
[CrossRef]

Pauciullo, A.

G. Fornaro, A. Pauciullo, and E. Sansosti, “Phase difference-based multichannel phase unwrapping,” IEEE Trans. Image Process. 14, 960–972 (2005).
[CrossRef]

Pezzati, L.

A. Capanni, L. Pezzati, D. Bertani, M. Cetica, and F. Francini, “Phase-shifting speckle interferometry: a noise reduction filter for phase unwrapping,” Opt. Eng. 36, 2466–2472 (1997).
[CrossRef]

Pritt, M. D.

D. C. Ghiglia and M. D. Pritt, Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software (Wiley, 1998).

Qian, K. M.

Rastogi, P.

S. S. Gorthi and P. Rastogi, “Fringe projection techniques: whither we are?” Opt. Lasers Eng. 48, 133–140 (2010).
[CrossRef]

Reigber, A.

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 Sensing 36, 1173 (1998).
[CrossRef]

Romero, L. A.

Sansosti, E.

G. Fornaro, A. Pauciullo, and E. Sansosti, “Phase difference-based multichannel phase unwrapping,” IEEE Trans. Image Process. 14, 960–972 (2005).
[CrossRef]

Song, M.

F. Chen, G. M. Brown, and M. Song, “Overview of three-dimensional shape measurement using optical methods,” Opt. Eng. 39, 10–22 (2000).
[CrossRef]

Suchandt, S.

Wang, H.

Wang, Z. Y.

Xiang, Q. S.

L. An, Q. S. Xiang, and S. Chavez, “A fast implementation of the minimum spanning tree method for phase unwrapping,” IEEE Trans. Med. Imaging 19, 805–808 (2000).
[CrossRef]

Zebker, H. A.

ACM Comput. Surv. (1)

V. Chandola, A. Banerjee, and V. Kumar, “Anomaly detection: a survey,” ACM Comput. Surv. 41, 1–58 (2009).
[CrossRef]

Appl. Opt. (5)

IEEE Trans. Geosci. Remote Sensing (2)

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 Sensing 36, 1173 (1998).
[CrossRef]

M. Costantini, “A novel phase unwrapping method based on network programming,” IEEE Trans. Geosci. Remote Sensing 36, 813–821 (1998).
[CrossRef]

IEEE Trans. Image Process. (2)

J. M. N. Leitão and M. A. T. Figueiredo, “Absolute phase image reconstruction: a stochastic nonlinear filtering approach,” IEEE Trans. Image Process. 7, 868–882 (1998).
[CrossRef]

G. Fornaro, A. Pauciullo, and E. Sansosti, “Phase difference-based multichannel phase unwrapping,” IEEE Trans. Image Process. 14, 960–972 (2005).
[CrossRef]

IEEE Trans. Med. Imaging (2)

L. An, Q. S. Xiang, and S. Chavez, “A fast implementation of the minimum spanning tree method for phase unwrapping,” IEEE Trans. Med. Imaging 19, 805–808 (2000).
[CrossRef]

Z. P. Liang, “A model-based method for phase unwrapping,” IEEE Trans. Med. Imaging 15, 893–897 (1996).
[CrossRef]

IEEE Trans. Signal Process. (1)

G. Nico, G. Palubinskas, and M. Datcu, “Bayesian approaches to phase unwrapping: theoretical study,” IEEE Trans. Signal Process. 48, 2545–2556 (2000).
[CrossRef]

J. Opt. Soc. Am. A (3)

J. Opt. Soc. Am. A. (1)

G. Nico, “Noise-residue filtering of interferometric phase images,” J. Opt. Soc. Am. A. 17, 1962–1974 (2000).
[CrossRef]

Opt. Eng. (2)

A. Capanni, L. Pezzati, D. Bertani, M. Cetica, and F. Francini, “Phase-shifting speckle interferometry: a noise reduction filter for phase unwrapping,” Opt. Eng. 36, 2466–2472 (1997).
[CrossRef]

F. Chen, G. M. Brown, and M. Song, “Overview of three-dimensional shape measurement using optical methods,” Opt. Eng. 39, 10–22 (2000).
[CrossRef]

Opt. Lasers Eng. (1)

S. S. Gorthi and P. Rastogi, “Fringe projection techniques: whither we are?” Opt. Lasers Eng. 48, 133–140 (2010).
[CrossRef]

Opt. Lett. (1)

Other (5)

cmax is the cluster in which the number of members is biggest.

D. C. Ghiglia and M. D. Pritt, Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software (Wiley, 1998).

J. Jiang and J. Cheng, “Noise-residue filtering based on unsupervised clustering for phase unwrapping,” in Proceedings of 5th International Symposium on Visual Computing, M.Z.Nashed, ed. (Springer, 2009), pp. 719–727.

P. Berkhin, Survey of Clustering Data Mining Techniques (Springer, 2002).

cmin is the cluster in which the number of members is smallest.

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