Abstract

A computational integral imaging reconstruction technique can reconstruct a set of plane images of three-dimensional (3-D) objects along the output plane, in which only the plane object image (POI) reconstructed on the right planes where the objects were positioned is highly focused, whereas the other POIs reconstructed away from these planes are unfocused and blurred. In fact, these blurred POIs act as additional noises to other object images reconstructed on different output planes, so that the resolution of reconstructed object images should be considerably deteriorated. In this paper, a novel approach is proposed to effectively reduce the blurred images occurring in the focused POIs by employing a blur metric. From the estimated blur metric of each reconstructed POI, the right output planes where the objects were located can be detected. In addition, with an estimated blur metric, focused POIs can be adaptively eroded by a simple gray level erosion operation because it reduces regional expansion caused by the blur effect. The gray values of the eroded POIs are then finally remapped by referencing the original POIs. Some experiments revealed an average increase of 1.95dB in the peak signal-to-noise ratio in the remapped POIs compared with that of the originally reconstructed POIs, and that the original forms of the object images in the remapped POIs could be preserved even after they had gone through an erosion operation. This feasibility test of the proposed scheme finally suggests a possibility of its application to robust detection and recognition of 3-D objects in a scene.

© 2008 Optical Society of America

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  1. G. Lippmann, “La photographie integrale,” Comp. Rend. 146, 446-451 (1908).
  2. F. Okano, H. Hoshino, J. Arai, and I. Yuyama, “Real-time pickup method for a three-dimensional image based on integral photography,” Appl. Opt. 36, 1598-1603 (1997).
    [CrossRef] [PubMed]
  3. S. W. Min, B. Javidi, and B. Lee, “Enhanced three-dimensional integral imaging system by use of double display devices,” Appl. Opt. 42, 4186-4195 (2003).
    [CrossRef] [PubMed]
  4. S. Hong, J. Jang, and B. Javidi, “Three-dimensional volumetric object reconstruction using computational integral imaging,” Opt. Express 12, 483-491 (2004).
    [CrossRef] [PubMed]
  5. D. H. Shin, E. S. Kim, and B. Lee, “Computational reconstruction technique of three-dimensional object in integral imaging using a lenslet array,” Jpn. J. Appl. Phys. 44, 8016-8018 (2005).
    [CrossRef]
  6. B. Javidi, R. Ponce-Díaz, and S. H. Hong, “Three-dimensional recognition of occluded objects by using computational integral imaging,” Opt. Lett. 31, 1106-1108 (2006).
    [CrossRef] [PubMed]
  7. Y. Frauel and B. Javidi, “Digital three-dimensional image correlation by use of computer reconstructed integral imaging,” Appl. Opt. 41, 5488-5496 (2002).
    [CrossRef] [PubMed]
  8. J. Park, J. Kim, and B. Lee, “Three-dimensional optical correlator using a sub-image array,” Opt. Express 13, 5116-5126(2005).
    [CrossRef] [PubMed]
  9. J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced three-dimensional image correlator using computationally reconstructed integral images,” Opt. Commun. 276, 72-79 (2007).
    [CrossRef]
  10. D. C. Hwang, D. H. Shin, and E. S. Kim, “Depth extraction by use of a computational integral imaging reconstruction technique,” in Proceedings of Asia Display 2007 (Society for Information Display, 2007), pp. 1961-1966.
  11. J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced computational integral imaging reconstruction using intermediate-view reconstruction technique,” Opt. Eng. 45, 117004 (2006).
    [CrossRef]
  12. S.-H. Hong and B. Javidi, “Improved resolution 3-D object reconstruction using computational integral imaging with time multiplexing,” Opt. Express 12, 4579-4588 (2004).
    [CrossRef] [PubMed]
  13. J. B. Hyun, D. C. Hwang, D. H. Shin, and E. S. Kim, “Curved computational integral imaging reconstruction technique for resolution-enhanced display of three-dimensional object images,” Appl. Opt. 46, 7697-7708 (2007).
    [CrossRef] [PubMed]
  14. P. Marziliano, F. Dufaux, S. Winkler, and T. Ebrahimi, “A no-reference perceptual blur metric,” in Proceedings of IEEE Conference on Image Processing (IEEE, 2002), pp. 57-60.
  15. Y. C. Chung, J. M. Wang, R. R. Bailey, and S. W. Chen, “A non-parametric blur measure based on edge analysis for image processing applications,” in Proceedings of IEEE Conference on Cybernetics and Intelligent Systems (IEEE, 2004), pp. 356-360.
  16. R. Youmaran and A. Adler, “Using red-eye to improve face detection in low quality video image,” in Proceeding of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 2006), pp. 1940-1943.
    [CrossRef]

2007

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced three-dimensional image correlator using computationally reconstructed integral images,” Opt. Commun. 276, 72-79 (2007).
[CrossRef]

J. B. Hyun, D. C. Hwang, D. H. Shin, and E. S. Kim, “Curved computational integral imaging reconstruction technique for resolution-enhanced display of three-dimensional object images,” Appl. Opt. 46, 7697-7708 (2007).
[CrossRef] [PubMed]

2006

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced computational integral imaging reconstruction using intermediate-view reconstruction technique,” Opt. Eng. 45, 117004 (2006).
[CrossRef]

B. Javidi, R. Ponce-Díaz, and S. H. Hong, “Three-dimensional recognition of occluded objects by using computational integral imaging,” Opt. Lett. 31, 1106-1108 (2006).
[CrossRef] [PubMed]

2005

D. H. Shin, E. S. Kim, and B. Lee, “Computational reconstruction technique of three-dimensional object in integral imaging using a lenslet array,” Jpn. J. Appl. Phys. 44, 8016-8018 (2005).
[CrossRef]

J. Park, J. Kim, and B. Lee, “Three-dimensional optical correlator using a sub-image array,” Opt. Express 13, 5116-5126(2005).
[CrossRef] [PubMed]

2004

2003

2002

1997

1908

G. Lippmann, “La photographie integrale,” Comp. Rend. 146, 446-451 (1908).

Adler, A.

R. Youmaran and A. Adler, “Using red-eye to improve face detection in low quality video image,” in Proceeding of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 2006), pp. 1940-1943.
[CrossRef]

Arai, J.

Bailey, R. R.

Y. C. Chung, J. M. Wang, R. R. Bailey, and S. W. Chen, “A non-parametric blur measure based on edge analysis for image processing applications,” in Proceedings of IEEE Conference on Cybernetics and Intelligent Systems (IEEE, 2004), pp. 356-360.

Chen, S. W.

Y. C. Chung, J. M. Wang, R. R. Bailey, and S. W. Chen, “A non-parametric blur measure based on edge analysis for image processing applications,” in Proceedings of IEEE Conference on Cybernetics and Intelligent Systems (IEEE, 2004), pp. 356-360.

Chung, Y. C.

Y. C. Chung, J. M. Wang, R. R. Bailey, and S. W. Chen, “A non-parametric blur measure based on edge analysis for image processing applications,” in Proceedings of IEEE Conference on Cybernetics and Intelligent Systems (IEEE, 2004), pp. 356-360.

Dufaux, F.

P. Marziliano, F. Dufaux, S. Winkler, and T. Ebrahimi, “A no-reference perceptual blur metric,” in Proceedings of IEEE Conference on Image Processing (IEEE, 2002), pp. 57-60.

Ebrahimi, T.

P. Marziliano, F. Dufaux, S. Winkler, and T. Ebrahimi, “A no-reference perceptual blur metric,” in Proceedings of IEEE Conference on Image Processing (IEEE, 2002), pp. 57-60.

Frauel, Y.

Hong, S.

Hong, S. H.

Hong, S.-H.

Hoshino, H.

Hwang, D. C.

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced three-dimensional image correlator using computationally reconstructed integral images,” Opt. Commun. 276, 72-79 (2007).
[CrossRef]

J. B. Hyun, D. C. Hwang, D. H. Shin, and E. S. Kim, “Curved computational integral imaging reconstruction technique for resolution-enhanced display of three-dimensional object images,” Appl. Opt. 46, 7697-7708 (2007).
[CrossRef] [PubMed]

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced computational integral imaging reconstruction using intermediate-view reconstruction technique,” Opt. Eng. 45, 117004 (2006).
[CrossRef]

D. C. Hwang, D. H. Shin, and E. S. Kim, “Depth extraction by use of a computational integral imaging reconstruction technique,” in Proceedings of Asia Display 2007 (Society for Information Display, 2007), pp. 1961-1966.

Hyun, J. B.

Jang, J.

Javidi, B.

Kim, E. S.

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced three-dimensional image correlator using computationally reconstructed integral images,” Opt. Commun. 276, 72-79 (2007).
[CrossRef]

J. B. Hyun, D. C. Hwang, D. H. Shin, and E. S. Kim, “Curved computational integral imaging reconstruction technique for resolution-enhanced display of three-dimensional object images,” Appl. Opt. 46, 7697-7708 (2007).
[CrossRef] [PubMed]

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced computational integral imaging reconstruction using intermediate-view reconstruction technique,” Opt. Eng. 45, 117004 (2006).
[CrossRef]

D. H. Shin, E. S. Kim, and B. Lee, “Computational reconstruction technique of three-dimensional object in integral imaging using a lenslet array,” Jpn. J. Appl. Phys. 44, 8016-8018 (2005).
[CrossRef]

D. C. Hwang, D. H. Shin, and E. S. Kim, “Depth extraction by use of a computational integral imaging reconstruction technique,” in Proceedings of Asia Display 2007 (Society for Information Display, 2007), pp. 1961-1966.

Kim, J.

Lee, B.

Lippmann, G.

G. Lippmann, “La photographie integrale,” Comp. Rend. 146, 446-451 (1908).

Marziliano, P.

P. Marziliano, F. Dufaux, S. Winkler, and T. Ebrahimi, “A no-reference perceptual blur metric,” in Proceedings of IEEE Conference on Image Processing (IEEE, 2002), pp. 57-60.

Min, S. W.

Okano, F.

Park, J.

Park, J. S.

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced three-dimensional image correlator using computationally reconstructed integral images,” Opt. Commun. 276, 72-79 (2007).
[CrossRef]

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced computational integral imaging reconstruction using intermediate-view reconstruction technique,” Opt. Eng. 45, 117004 (2006).
[CrossRef]

Ponce-Díaz, R.

Shin, D. H.

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced three-dimensional image correlator using computationally reconstructed integral images,” Opt. Commun. 276, 72-79 (2007).
[CrossRef]

J. B. Hyun, D. C. Hwang, D. H. Shin, and E. S. Kim, “Curved computational integral imaging reconstruction technique for resolution-enhanced display of three-dimensional object images,” Appl. Opt. 46, 7697-7708 (2007).
[CrossRef] [PubMed]

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced computational integral imaging reconstruction using intermediate-view reconstruction technique,” Opt. Eng. 45, 117004 (2006).
[CrossRef]

D. H. Shin, E. S. Kim, and B. Lee, “Computational reconstruction technique of three-dimensional object in integral imaging using a lenslet array,” Jpn. J. Appl. Phys. 44, 8016-8018 (2005).
[CrossRef]

D. C. Hwang, D. H. Shin, and E. S. Kim, “Depth extraction by use of a computational integral imaging reconstruction technique,” in Proceedings of Asia Display 2007 (Society for Information Display, 2007), pp. 1961-1966.

Wang, J. M.

Y. C. Chung, J. M. Wang, R. R. Bailey, and S. W. Chen, “A non-parametric blur measure based on edge analysis for image processing applications,” in Proceedings of IEEE Conference on Cybernetics and Intelligent Systems (IEEE, 2004), pp. 356-360.

Winkler, S.

P. Marziliano, F. Dufaux, S. Winkler, and T. Ebrahimi, “A no-reference perceptual blur metric,” in Proceedings of IEEE Conference on Image Processing (IEEE, 2002), pp. 57-60.

Youmaran, R.

R. Youmaran and A. Adler, “Using red-eye to improve face detection in low quality video image,” in Proceeding of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 2006), pp. 1940-1943.
[CrossRef]

Yuyama, I.

Appl. Opt.

Comp. Rend.

G. Lippmann, “La photographie integrale,” Comp. Rend. 146, 446-451 (1908).

Jpn. J. Appl. Phys.

D. H. Shin, E. S. Kim, and B. Lee, “Computational reconstruction technique of three-dimensional object in integral imaging using a lenslet array,” Jpn. J. Appl. Phys. 44, 8016-8018 (2005).
[CrossRef]

Opt. Commun.

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced three-dimensional image correlator using computationally reconstructed integral images,” Opt. Commun. 276, 72-79 (2007).
[CrossRef]

Opt. Eng.

J. S. Park, D. C. Hwang, D. H. Shin, and E. S. Kim, “Resolution-enhanced computational integral imaging reconstruction using intermediate-view reconstruction technique,” Opt. Eng. 45, 117004 (2006).
[CrossRef]

Opt. Express

Opt. Lett.

Other

D. C. Hwang, D. H. Shin, and E. S. Kim, “Depth extraction by use of a computational integral imaging reconstruction technique,” in Proceedings of Asia Display 2007 (Society for Information Display, 2007), pp. 1961-1966.

P. Marziliano, F. Dufaux, S. Winkler, and T. Ebrahimi, “A no-reference perceptual blur metric,” in Proceedings of IEEE Conference on Image Processing (IEEE, 2002), pp. 57-60.

Y. C. Chung, J. M. Wang, R. R. Bailey, and S. W. Chen, “A non-parametric blur measure based on edge analysis for image processing applications,” in Proceedings of IEEE Conference on Cybernetics and Intelligent Systems (IEEE, 2004), pp. 356-360.

R. Youmaran and A. Adler, “Using red-eye to improve face detection in low quality video image,” in Proceeding of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE, 2006), pp. 1940-1943.
[CrossRef]

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Figures (18)

Fig. 1
Fig. 1

Schematic diagram of the integral imaging system: optical pickup and OIIR.

Fig. 2
Fig. 2

Schematic diagram of the integral imaging system: computational pickup and CIIR.

Fig. 3
Fig. 3

Flowchart of the proposed scheme.

Fig. 4
Fig. 4

System diagram of computational pickup of a test 3-D object.

Fig. 5
Fig. 5

Computer-generated elemental images of the test 3-D object.

Fig. 6
Fig. 6

Schematic of the CIIR-based reconstruction of object images from the picked-up elemental images.

Fig. 7
Fig. 7

Reconstructed plane images of the reference object at some distances of z.

Fig. 8
Fig. 8

Detailed procedure of unfocused noises removal with a measured blur metric.

Fig. 9
Fig. 9

Illustration of the ψ-axis establishment for P e ( x e , y e ) .

Fig. 10
Fig. 10

Blur measure of the edges in plane images reconstructed at some distances of z.

Fig. 11
Fig. 11

Original POIs and their eroded POIs.

Fig. 12
Fig. 12

Remapped POIs.

Fig. 13
Fig. 13

PSNR comparison between the originally reconstructed POIs and the remapped POIs.

Fig. 14
Fig. 14

First column, templates of Targets 1–4; second column, template matching with original POIs; third column, template matching with remapped POIs.

Fig. 15
Fig. 15

System diagram of computational pickup of a test 3-D object.

Fig. 16
Fig. 16

Computer-generated elemental images of the reference objects.

Fig. 17
Fig. 17

Reconstructed plane images of the reference object at arbitrary distances of z.

Fig. 18
Fig. 18

Remapped POIs of overlapped objects.

Tables (2)

Tables Icon

Table 1 Transformed Erosion Parameters ( L = 255 , K = 80 )

Tables Icon

Table 2 Transformed Erosion Parameters ( L = 192 , K = 109 )

Equations (12)

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I ( x , y ) = [ G x G y ] = [ x I ( x , y ) y I ( x , y ) ] .
| I ( x , y ) | = G x 2 + G y 2 ,
θ ( x , y ) = tan 1 ( G y G x ) .
σ 2 ( p e ) = 1 | m r m l | Ψ = m l m r | I ( Ψ ) | Ψ 2 .
β ( p e ) = η β σ ( p e ) σ max + ( 1 η β ) | I ( p e ) | | I ( p e ) | max ,
β ( p e ) = 1 2 ( σ ( p e ) σ max + | I ( p e ) | | I ( p e ) | max ) .
β MBM = α × β mean = M N × β mean .
( f Θ b ) ( s , t ) = min { f ( s + x , t + y ) b ( x , y ) | ( s + x ) , ( t + y ) D f and ( x , y ) D b } .
β MBM = β MBM × 255 ,
k = L / max ( β MBM ) , k :     constant ,
Erosion parameter     T = k β MBM .
POI e ( x , y ) = { POI o ( x , y ) if     POI e ( x , y ) > 0 0 otherwise .

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