Abstract

We propose an artifact analysis in computational integral imaging and the image enhancement method based on the analysis using the smooth windowing technique. Blurring and lenslet artifacts, which are major problems in computational integral imaging, are defined and analyzed using a signal model. Applying a smooth and continuous window such as the triangular window to computational integral imaging reconstruction provides a dramatic improvement in terms of image quality. Experimental results are presented to show the validity of our method. To our best knowledge, this is the first trial to control a window function in computational integral imaging.

© 2011 Optical Society of America

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References

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Arimoto, H.

Daneshpanah, M.

Hong, K.

Hong, S.-H.

Jang, J.-S.

Javidi, B.

Kim, E.-S.

Lee, B.

Lippmann, G.

G. Lippmann, C. R. Acad. Sci. 146, 446 (1908).

Martinez-Corral, M.

Martinez-Cuenca, R.

Moon, I.

Navarro, H.

Park, J.-H.

Piao, Y.

Ponce-Díaz, R.

Saavedra, G.

Shin, D.-H.

Stern, A.

A. Stern and B. Javidi, Proc. IEEE 94, 591 (2006).
[CrossRef]

Yoo, H.

Zhang, M.

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Figures (6)

Fig. 1
Fig. 1

CIIR and its artifacts on reconstructed images.

Fig. 2
Fig. 2

(a) Integral imaging system and (b) its signal model.

Fig. 3
Fig. 3

(a) Illustration of blurring where z = z 0 and z = z 0 ± Δ z ; (b) resulting signal from overlapping where z = z 0 = 3 g ; (c) resulting signals from overlapping where z 0 = 3 g and Δ z = g .

Fig. 4
Fig. 4

(a)  c k for rectangular window; (b)  c k for triangular window; (c) overlapping by use of triangular window, where z 0 = 3 g and z = 2 g .

Fig. 5
Fig. 5

(a) Overlapping with rectangular window, where z 0 = 3 g and z = 4 g . (b) Overlapping with triangular window.

Fig. 6
Fig. 6

Reconstructed images using rectangular window (left) and triangular window (right). The images of the top row are reconstructed at z = z 0 ( 20 mm ) and the images of the bottom row are reconstructed at z = z 0 + 5 mm .

Equations (5)

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r z ( x ) = f z ( x ) i = 0 N 1 π i ( x w ) = f z ( x ) s π ( x ) ,
r z ( x ) = f ( x ) * k = M 0 / 2 M 0 / 2 δ ( x k Δ x ) = f ( x ) * s δ ( x ) ,
r z ( x ) = f ( x ) * k = M 0 / 2 M 0 / 2 c k δ ( x k Δ x ) .
c k = π 0 ( k a / w ) , k = M 0 / 2 , , M 0 / 2 .
c k = Λ 0 ( k a / w ) , k = M 0 / 2 , , M 0 / 2 ,

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