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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 51, Iss. 13 — May. 1, 2012
  • pp: 2491–2496

Optical compressive change and motion detection

Yuval Kashter, Ofer Levi, and Adrian Stern  »View Author Affiliations


Applied Optics, Vol. 51, Issue 13, pp. 2491-2496 (2012)
http://dx.doi.org/10.1364/AO.51.002491


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Abstract

Localization information of moving and changing objects, as commonly extracted from video sequences, is typically very sparse with respect to the full data frames, thus fulfilling one of the basic conditions of compressive sensing theory. Motivated by this observation, we developed an optical compressive change and motion-sensing technique that detects the location of moving objects by using a significantly fewer samples than conventionally taken. We present examples of motion detection and motion tracking with over two orders of magnitude fewer samples than required with conventional systems.

© 2012 Optical Society of America

OCIS Codes
(110.1758) Imaging systems : Computational imaging
(110.4153) Imaging systems : Motion estimation and optical flow
(150.6044) Machine vision : Smart cameras

ToC Category:
Imaging Systems

History
Original Manuscript: January 23, 2012
Revised Manuscript: March 12, 2012
Manuscript Accepted: March 23, 2012
Published: May 1, 2012

Citation
Yuval Kashter, Ofer Levi, and Adrian Stern, "Optical compressive change and motion detection," Appl. Opt. 51, 2491-2496 (2012)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-51-13-2491


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References

  1. D. Donoho, “Compressed sensing,” IEEE Trans. Inf. Theory 52, 1289–1306 (2006). [CrossRef]
  2. E. Candès, J. Romberg, and T. Tao, “Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inf. Theory 52, 489–509 (2006). [CrossRef]
  3. A. Stern and B. Javidi, “Random projections imaging with extended space-bandwidth product,” J. Disp. Technol. 3, 315–320 (2007). [CrossRef]
  4. F. Magalhães, F. M. Araújo, M. V. Correia, M. Abolbashari, and F. Farahi, “Active illumination single pixel camera based on compressed sensing,” Appl. Opt. 50, 405–414 (2011). [CrossRef]
  5. D. Takhar, J. Laska, M. B. Wakin, M. F. Duarte, D. Baron, S. Sarvotham, K. Kelly, and R. G. Baraniuk, “A new compressive imaging camera architecture using optical-domain compression,” in Proceedings of SPIE-IS&T on Electronic Imaging (IEEE, 2006), pp. 43.
  6. Y. Rivenson, A. Stern, and B. Javidi, “Single exposure super-resolution compressive imaging by double phase encoding,” Opt. Express 18, 15094–15103 (2010). [CrossRef]
  7. S. Gazit, A. Szameit, Y. C. Eldar, and M. Segev, “Super-resolution and reconstruction of sparse sub-wavelength images,” Opt. Express 17, 23920–23946 (2009). [CrossRef]
  8. Y. Shechtman, Y. C. Eldar, A. Szameit, and M. Segev, “Sparsity based sub-wavelength imaging with partially incoherent light via quadratic compressed sensing,” Opt. Express 19, 14807–14822 (2011). [CrossRef]
  9. A. Wagadarikar, R. John, R. Willett, and D. Brady, “Single disperser design for coded aperture snapshot spectral imaging,” Appl. Opt. 47, B44–B51 (2008). [CrossRef]
  10. Y. Rivenson, A. Stern, and B. Javidi, “Compressive fresnel holography,” J. Disp. Technol. 6, 506–509 (2010). [CrossRef]
  11. R. M. Willett, R. F. Marcia, and J. M. Nichols, “Compressed sensing for practical optical imaging systems: a tutorial,” Opt. Eng. 50, 072601 (2011). [CrossRef]
  12. R. F. Marcia, Z. T. Harmany, and R. M. Willet, “Compressive coded aperture imaging,” in Proceedings of SPIE-IS&T on Electronic Imaging (IEEE, 2009), vol. 7245.
  13. T. Osman, P. K. Poon, D. Townsend, S. Wehrwein, A. Mariano, M. Stenner, and M. E. Gehm, “Experimental demonstration of compressive target tracking,” in Computational Optical Sensing and Imaging, OSA Technical Digest (CD) (Optical Society of America, 2011), paper CMB2.
  14. A. Stern, “Compressed imaging system with linear sensors,” Opt. Lett. 32, 3077–3079 (2007). [CrossRef]
  15. Y. Rivenson, A. Stern, and J. Rosen, “Compressive multiple view projection incoherent holography,” Opt. Express 19, 6109–6118 (2011). [CrossRef]
  16. D. Brady, K. Choi, D. Marks, R. Horisaki, and S. Lim, “Compressive holography,” Opt. Express 17, 13040–13049 (2009). [CrossRef]
  17. Y. Rivenson and A. Stern, “An efficient method for multi-dimensional compressive imaging,” in Computational Optical Sensing and Imaging, Technical Digest (CD) (Optical Society of America, 2009), paper CTuA4.
  18. W. H. Steier and R. K. Shori, “Optical Hough transform,” Appl. Opt. 25, 2734–2738 (1986). [CrossRef]
  19. A. K. Jain, Fundamentals of Image Processing (Prentice-Hall, 1989).
  20. S. Evladov, O. Levi, and A. Stern, “Progressive compressive imaging from Radon projections,” Opt. Express 20, 4260–4271 (2012). [CrossRef]
  21. 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]

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