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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 19, Iss. 13 — Jun. 20, 2011
  • pp: 12540–12550

Preconditioning for multiplexed imaging with spatially coded PSFs

Ryoichi Horisaki and Jun Tanida  »View Author Affiliations


Optics Express, Vol. 19, Issue 13, pp. 12540-12550 (2011)
http://dx.doi.org/10.1364/OE.19.012540


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Abstract

We propose a preconditioning method to improve the convergence of iterative reconstruction algorithms in multiplexed imaging based on convolution-based compressive sensing with spatially coded point spread functions (PSFs). The system matrix is converted to improve the condition number with a preconditioner matrix. The preconditioner matrix is calculated by Tikhonov regularization in the frequency domain. The method was demonstrated with simulations and an experiment involving a range detection system with a grating based on the multiplexed imaging framework. The results of the demonstrations showed improved reconstruction fidelity by using the proposed preconditioning method.

© 2011 OSA

OCIS Codes
(110.1758) Imaging systems : Computational imaging
(110.3010) Imaging systems : Image reconstruction techniques

ToC Category:
Imaging Systems

History
Original Manuscript: April 7, 2011
Revised Manuscript: June 1, 2011
Manuscript Accepted: June 2, 2011
Published: June 14, 2011

Citation
Ryoichi Horisaki and Jun Tanida, "Preconditioning for multiplexed imaging with spatially coded PSFs," Opt. Express 19, 12540-12550 (2011)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-19-13-12540


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References

  1. A. Kak and M. Slaney, Principles of Computerized Tomographic Imaging (IEEE Press, 1988).
  2. D. J. Brady, Optical imaging and spectroscopy (Wiley-OSA, 2009). [CrossRef]
  3. D. L. Donoho, “Compressed sensing,” IEEE Trans. Info. Theory 52, 1289–1306 (2006). [CrossRef]
  4. R. Baraniuk, “Compressive sensing,” IEEE Sig. Process. Mag. 24, 118–121 (2007). [CrossRef]
  5. E. J. Candes and M. B. Wakin, “An introduction to compressive sampling,” IEEE Sig. Process. Mag. 25, 21–30 (2008). [CrossRef]
  6. D. J. Brady, K. Choi, D. L. Marks, R. Horisaki, and S. Lim, “Compressive holography,” Opt. Express 17, 13040–13049 (2009). [CrossRef] [PubMed]
  7. M. E. Gehm, R. John, D. J. Brady, R. M. Willett, and T. J. Schulz, “Single-shot compressive spectral imaging with a dual-disperser architecture,” Opt. Express 15, 14013–14027 (2007). [CrossRef] [PubMed]
  8. R. Horisaki, K. Choi, J. Hahn, J. Tanida, and D. J. Brady, “Generalized sampling using a compound-eye imaging system for multi-dimensional object acquisition,” Opt. Express 18, 19367–19378 (2010). [CrossRef] [PubMed]
  9. M. Shankar, N. P. Pitsianis, and D. J. Brady, “Compressive video sensors using multichannel imagers,” Appl. Opt. 49, B9–B17 (2010). [CrossRef] [PubMed]
  10. A. Ashok and M. A. Neifeld, “Compressive light field imaging,” Proc. SPIE 7690, 76900Q (2010). [CrossRef]
  11. J. Romberg, “Compressive sensing by random convolution,” SIAM J. Imaging Sci. 2, 1098–1128 (2009). [CrossRef]
  12. R. F. Marcia and R. M. Willett, “Compressive coded aperture superresolution image reconstruction,” in “IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008),” (2008), pp. 833–836.
  13. Y. Rivenson, A. Stern, and B. Javidi, “Single exposure super-resolution compressive imaging by double phase encoding,” Opt. Express 18, 15094–15103 (2010). [CrossRef] [PubMed]
  14. J. Hahn, S. Lim, K. Choi, R. Horisaki, and D. J. Brady, “Video-rate compressive holographic microscopic tomography,” Opt. Express 19, 7289–7298 (2011). [CrossRef] [PubMed]
  15. R. Horisaki and J. Tanida, “Multi-channel data acquisition using multiplexed imaging with spatial encoding,” Opt. Express 18, 23041–23053 (2010). [CrossRef] [PubMed]
  16. N. Nguyen, P. Milanfar, S. Member, and G. Golub, “A computationally efficient superresolution image reconstruction algorithm,” IEEE Trans. Image Proc. 10, 573–583 (2001). [CrossRef]
  17. K. Choi, R. Horisaki, J. Hahn, S. Lim, D. L. Marks, T. J. Schulz, and D. J. Brady, “Compressive holography of diffuse objects,” Appl. Opt. 49, H1–H10 (2010). [CrossRef] [PubMed]
  18. A. Ashok and M. A. Neifeld, “Pseudorandom phase masks for superresolution imaging from subpixel shifting,” Appl. Opt. 46, 2256–2268 (2007). [CrossRef] [PubMed]
  19. A. Mahalanobis, M. Neifeld, V. K. Bhagavatula, T. Haberfelde, and D. Brady, “Off-axis sparse aperture imaging using phase optimization techniques for application in wide-area imaging systems,” Appl. Opt. 48, 5212–5224 (2009). [CrossRef] [PubMed]
  20. J. M. Bioucas-Dias and M. A. T. Figueiredo, “A new TwIST: Two-step iterative shrinkage/thresholding algorithms for image restoration,” IEEE Trans. Image Proc. 16, 2992–3004 (2007). [CrossRef]
  21. L. I. Rudin, S. Osher, and E. Fatemi, “Nonlinear total variation based noise removal algorithms,” Phys. D 60, 259–268 (1992). [CrossRef]
  22. “Spectral image database,” http://spectral.joensuu.fi/multispectral/spectralimages.php .

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