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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: James C. Wyant
  • Vol. 47, Iss. 32 — Nov. 10, 2008
  • pp: 6079–6087

Resolution-enhanced subpixel phase retrieval method

Xiaojun-Hu, Shengyi-Li, and Yulie-Wu  »View Author Affiliations


Applied Optics, Vol. 47, Issue 32, pp. 6079-6087 (2008)
http://dx.doi.org/10.1364/AO.47.006079


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Abstract

Phase retrieval is a wavefront sensing method that uses a series of intensity images to reconstruct the wavefront. The resolution of phase retrieval testing is limited mainly by the resolution of intensity images captured by CCD cameras. A subpixel phase retrieval method is presented to retrieve the wave field at subpixel resolution by using the information of a sequence of low-resolution images captured along the propagation direction. In this method, the sampling interval for the wave field under test is smaller than the CCD pixel size in phase reconstruction. The wave field is recovered at subpixel resolution by utilizing the energy conservation relationship between CCD pixels and their subpixels by the subpixel phase retrieval (SPR) algorithm. Numerical experiments have shown that more than a fourfold resolution enhancement can be achieved. The method has also been studied in some experiments under noisy and off-axis conditions. A mirror surface testing experiment was conducted to demonstrate the performance of SPR in the real world. The results of these experiments have shown the effectiveness and robustness of this method. SPR allows low-resolution images to be used to retrieve high-resolution wave fields and will be useful in testing wave fields from large objects.

© 2008 Optical Society of America

OCIS Codes
(120.0120) Instrumentation, measurement, and metrology : Instrumentation, measurement, and metrology
(120.5050) Instrumentation, measurement, and metrology : Phase measurement

ToC Category:
Instrumentation, Measurement, and Metrology

History
Original Manuscript: February 25, 2008
Revised Manuscript: September 21, 2008
Manuscript Accepted: September 26, 2008
Published: November 7, 2008

Citation
Xiaojun-Hu , Shengyi-Li , and Yulie-Wu , "Resolution-enhanced subpixel phase retrieval method," Appl. Opt. 47, 6079-6087 (2008)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-47-32-6079


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References

  1. R. W. Gerchberg and W. O. Saxton, “A practical algorithm for the determination of phase from image and diffraction plane pictures,” Optik (Stuttgart) 35, 237-246 (1972).
  2. J. R. Fienup, “Phase retrieval algorithms: a comparison,” Appl. Opt. 21, 2758-2769 (1982). [CrossRef] [PubMed]
  3. G. Yang, B. Dong, B. Gu, J. Zhuang, and O. K. Erosy, “Gerchberg-Saxton and Yang-Gu algorithms for phase retrieval in a nonunitary transform system: a comparison,” Appl. Opt. 33, 209-218 (1994). [CrossRef] [PubMed]
  4. G. Pedrini, W. Osten and Y. Zhang. “Wave-front reconstruction from a sequence of interferograms recorded at different planes,” Opt. Lett. 30, 833-835 (2005). [CrossRef] [PubMed]
  5. J. R. Fienup, J. C. Marron, T. J. Schulz and J. H. Seldin, “Hubble Space telescope characterized by using phase-retrieval algorithms,” Appl. Opt. 32, 1747-1767 (1993). [CrossRef] [PubMed]
  6. M. O. Catherine, A. F. Jessica, “Phase retrieval camera optical testing of the Advanced Mirror System Demonstrator (AMSD),” Proc. SPIE 5487, 1744-1753 (2004).
  7. H. I. Campbell and A. H. S. Zhang, “Greenaway, generalized phase diversity for wave-front sensing,” Opt. Lett. 29, 2707-2709 (2004). [CrossRef] [PubMed]
  8. J. R. Fienup, “Phase retrieval for undersampled broadband images,” J. Opt. Soc. Am. A 16, 1831-1839 (1999). [CrossRef]
  9. S. C. Park, M. K. Park, and M. G. Kang, “Superresolution image reconstruction: a technical overview,” IEEE Signal Process. Mag. 20(3), 21-36 (2003). [CrossRef]
  10. S. Borman and R. L. Stevenson, “Superresolution from image sequences--a review,” Proceedings of the 1998 Midwest Symposium on Circuits and Systems (IEEE, 1998), pp. 374-378.
  11. M. Bertero and C. Demol, “Superresolution by data inversion,” in Progress in Optics, E. Wolf, ed. (Elsevier North-Holland, 1996), Vol. 36, pp. 129-178. [CrossRef]
  12. M. Elad and A. Feuer, “Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images,” IEEE Trans. Image Process. 6, 1646-1658 (1997). [CrossRef]
  13. M. Bierling, “Displacement estimation by hierarchical block matching,” Proc. SPIE 1001, 942-951 (1988).
  14. M. S. Alam, J. G. Bognar, R. C. Hardie, and B. J. Yasuda, “Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames,” IEEE Trans. Instrum. Meas. 49, 915-923 (2000). [CrossRef]
  15. D. Rajan and S. Chaudhuri, “Generalized interpolation and its applications in super-resolution imaging,” Image Vision Comput. 19, 957-969 (2001). [CrossRef]
  16. M. Elad and Y. Hel-Or, “A fast super-resolution reconstruction algorithm for pure translational motion and common space-invariant blur,” IEEE Trans. Image Process. 10, 1187-1193(2001). [CrossRef]
  17. H. Stark and P. Oskoui, “High resolution image recovery from image plane arrays, using convex projections,” J. Opt. Soc. Am. A 6, 1715-1726 (1989). [CrossRef] [PubMed]
  18. S. S. Young and R. G. Driggers, “Superresolution image reconstruction from a sequence of aliased imagery,” Appl. Opt. 45, 5073-5085 (2006). [CrossRef] [PubMed]
  19. P. Almoro, G. Pedrini, and W. Osten, “Complete wavefront reconstruction using sequential intensity measurements of a volume speckle field,” Appl. Opt 45, 8596-8605(2006). [CrossRef] [PubMed]
  20. G. R. Brady and J. R. Fienup, “Nonlinear optimization algorithm for retrieving the full complex pupil function,” Opt. Express 14, 474-486 (2006). [CrossRef] [PubMed]
  21. D. J. Shpak and A. Antoniou, “A generalized Remez method for the design of FIR digital filters,” IEEE Trans. Circuits Syst. 37, 161-174 (1990). [CrossRef]

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