OSA's Digital Library

Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 53, Iss. 13 — May. 1, 2014
  • pp: 2777–2786

Simultaneous reconstruction of multiple depth images without off-focus points in integral imaging using a graphics processing unit

Faliu Yi, Jieun Lee, and Inkyu Moon  »View Author Affiliations


Applied Optics, Vol. 53, Issue 13, pp. 2777-2786 (2014)
http://dx.doi.org/10.1364/AO.53.002777


View Full Text Article

Enhanced HTML    Acrobat PDF (1947 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

The reconstruction of multiple depth images with a ray back-propagation algorithm in three-dimensional (3D) computational integral imaging is computationally burdensome. Further, a reconstructed depth image consists of a focus and an off-focus area. Focus areas are 3D points on the surface of an object that are located at the reconstructed depth, while off-focus areas include 3D points in free-space that do not belong to any object surface in 3D space. Generally, without being removed, the presence of an off-focus area would adversely affect the high-level analysis of a 3D object, including its classification, recognition, and tracking. Here, we use a graphics processing unit (GPU) that supports parallel processing with multiple processors to simultaneously reconstruct multiple depth images using a lookup table containing the shifted values along the x and y directions for each elemental image in a given depth range. Moreover, each 3D point on a depth image can be measured by analyzing its statistical variance with its corresponding samples, which are captured by the two-dimensional (2D) elemental images. These statistical variances can be used to classify depth image pixels as either focus or off-focus points. At this stage, the measurement of focus and off-focus points in multiple depth images is also implemented in parallel on a GPU. Our proposed method is conducted based on the assumption that there is no occlusion of the 3D object during the capture stage of the integral imaging process. Experimental results have demonstrated that this method is capable of removing off-focus points in the reconstructed depth image. The results also showed that using a GPU to remove the off-focus points could greatly improve the overall computational speed compared with using a CPU.

© 2014 Optical Society of America

OCIS Codes
(100.6890) Image processing : Three-dimensional image processing
(110.6880) Imaging systems : Three-dimensional image acquisition
(170.3010) Medical optics and biotechnology : Image reconstruction techniques
(200.4960) Optics in computing : Parallel processing

ToC Category:
Optics in Computing

History
Original Manuscript: February 10, 2014
Revised Manuscript: March 26, 2014
Manuscript Accepted: March 28, 2014
Published: April 23, 2014

Virtual Issues
Vol. 9, Iss. 7 Virtual Journal for Biomedical Optics

Citation
Faliu Yi, Jieun Lee, and Inkyu Moon, "Simultaneous reconstruction of multiple depth images without off-focus points in integral imaging using a graphics processing unit," Appl. Opt. 53, 2777-2786 (2014)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-53-13-2777


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. G. Lippmann, “La photographie intégrale,” C. R. Acad. Sci. 146, 446–451 (1908).
  2. B. Javidi, F. Okano, and J.-Y. Son, eds., Three-Dimensional Imaging, Visualization, and Display Technologies (Springer, 2009).
  3. T. Mishina, “3D television system based on integral photography,” in Picture Coding Symposium (PCS) (IEEE, 2010), p. 20.
  4. O. Matoba, E. Tajahuerce, and B. Javidi, “Real-time three-dimensional object recognition with multiple perspectives imaging,” Appl. Opt. 40, 3318–3325 (2001). [CrossRef]
  5. A. Stern and B. Javidi, “Three-dimensional image sensing, visualization, and processing using integral imaging,” Proc. IEEE 94, 591–607 (2006). [CrossRef]
  6. Y. Igarishi, H. Murata, and M. Ueda, “3D display system using a computer-generated integral photograph,” Jpn. J. Appl. Phys. 17, 1683–1684 (1978).
  7. R. Martinez-Cuenca, G. Saavedra, M. Martinez-Corral, and B. Javidi, “Progress in 3-D multiperspective display by integral imaging,” Proc. IEEE 97, 1067–1077 (2009). [CrossRef]
  8. M. Levoy, “Light fields and computational imaging,” Computer 39, 46–55 (2006). [CrossRef]
  9. H. Hoshino, F. Okano, H. Isono, and I. Yuyama, “Analysis of resolution limitation of integral photography,” J. Opt. Soc. Am. A 15, 2059–2065 (1998). [CrossRef]
  10. C. Burckhardt, “Optimum parameters and resolution limitation of integral photography,” J. Opt. Soc. Am. 58, 71–76 (1968). [CrossRef]
  11. F. Okano, J. Arai, K. Mitani, and M. Okui, “Real-time integral imaging based on extremely high resolution video system,” Proc. IEEE 94, 490–501 (2006). [CrossRef]
  12. F. Okano, H. Hoshino, J. Arai, and I. Yuyama, “Three-dimensional video system based on integral photography,” Opt. Eng. 38, 1072–1077 (1999). [CrossRef]
  13. M. Forman, N. Davies, and M. McCormick, “Continuous parallax in discrete pixelated integral three-dimensional displays,” J. Opt. Soc. Am. A 20, 411–420 (2003). [CrossRef]
  14. B. Javidi, I. Moon, and S. Yeom, “Three-dimensional identification of biological microorganism using integral imaging,” Opt. Express 14, 12096–12108 (2006). [CrossRef]
  15. M. Cho, M. Daneshpanah, I. Moon, and B. Javidi, “Three-dimensional optical sensing and visualization using integral imaging,” Proc. IEEE 99, 556–575 (2011). [CrossRef]
  16. X. Xiao, B. Javidi, M. Manuel, and A. Stern, “Advances in three-dimensional integral imaging: sensing, display and application,” Appl. Opt. 52, 546–560 (2013). [CrossRef]
  17. I. Moon and B. Javidi, “Three-dimensional visualization of objects in scattering medium by use of computational integral imaging,” Opt. Express 16, 13080–13089 (2008). [CrossRef]
  18. B. Tavakoli, B. Javidi, and E. Watson, “Three-dimensional visualization by photon counting computational integral imaging,” Opt. Express 16, 4426–4436 (2008). [CrossRef]
  19. J. Park, K. Hong, and B. Lee, “Recent progress in three-dimensional information processing based on integral imaging,” Appl. Opt. 48, H77–H94 (2009). [CrossRef]
  20. H. Tan, J. Xia, Y. He, and Y. Guan, “A system for capturing, rendering and multiplexing images on multi-view autostereoscopic display,” in International Conference on Cyberworlds (2010), pp. 325–330.
  21. Y. Taguchi, T. Koike, K. Takahashi, and T. Naemura, “TransCAIP: a live 3D TV system using a camera array and an integral photography display with interactive control of viewing parameters,” IEEE Trans. Vis. Comput. Graph. 15, 841–852 (2009). [CrossRef]
  22. D. Michael, “Signal processing and general-purpose computing on GPUs,” IEEE Signal Process. Mag. 24, 109–114 (2007). [CrossRef]
  23. T. Balogh and P. Kovacs, “Real-time 3D light field transmission,” Proc. SPIE 7724, 5–11 (2010).
  24. D. Luebke and G. Humphreys, “How GPUs work,” IEEE Computer Society 40, 96–100 (2007).
  25. F. Yi, I. Moon, J. A. Lee, and B. Javidi, “Fast 3D computational integral imaging using graphics processing unit,” J. Disp. Technol. 8, 714–722 (2012).
  26. X. Xiao, M. Daneshpanah, and B. Javidi, “Occlusion removal using depth mapping in three-dimensional integral imaging,” J. Disp. Technol. 8, 483–490 (2012).
  27. R. C. Gonzalez and R. E. Woods, Digital Imaging Processing (Prentice Hall, 2002).

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