Abstract

Past research has demonstrated that a three-dimensional object scene can be converted into a digital hologram. Subsequently, the object scene can be reconstructed from the hologram with an iterative blind sectional image reconstruction (BSIR) method. However, the computation is extremely intensive, and escalated with the size of holograms. To overcome this problem, we propose a fast BSIR method that reconstructs sectional images with less out-of-focus haze. While the technique proposed here is applicable in general to holography for sectioning, we use holograms acquired by optical scanning holography as examples to show the method’s effectiveness.

© 2011 Optical Society of America

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References

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2009 (2)

2008 (2)

2002 (2)

1999 (1)

1997 (1)

Huisken, J.

Indebetouw, G.

Kim, T.

Kim, Y. S.

Lam, E.

Lam, E. Y.

Martínez-Corral, M.

Poon, T.-C.

Schilling, B. W.

Shinoda, K.

Stelzer, E. H. K.

Storrie, B.

Suzuki, Y.

Swoger, J.

Wu, M. H.

Zhang, X.

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Figures (5)

Fig. 1
Fig. 1

(a) Cosine hologram of the SH pattern. (b) Sine hologram of the SH pattern.

Fig. 2
Fig. 2

Edge count (y axis) versus reconstruction distance (x axis, in meters) for the SH hologram.

Fig. 3
Fig. 3

(a) Reconstruction of the SH hologram at 0.098 m with both in-focus and defocused contents. (b) Reconstruction of the SH hologram at 0.118 m with both in-focus and defocused contents. (c) Reconstruction of the SH hologram at 0.098 m with the proposed method (d) Reconstruction of the SH hologram at 0.118 m with the proposed method.

Fig. 4
Fig. 4

(a) Cosine hologram of the 3D scene “T3.” (b) Sine hologram of the 3D scene “T3.” (c) Reconstructed image at 0.33 m .

Fig. 5
Fig. 5

Reconstructed image at (a)  0.33 m , (b)  0.30 m , and (c)  0.36 m based on our proposed method.

Tables (1)

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Table 1 Number of CMs Involved in Deriving E ( x , y ; z r )

Equations (11)

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H ( x , y ) = i = 0 n 1 I 0 ( x , y ; z i ) * F ( x , y ; z i ) ,
F ( x , y ; z i ) = j λ z i exp { ( π NA 2 z i 2 + j π λ z i ) ( x 2 + y 2 ) } .
M r * γ = M r * M 0 Ψ 0 + M r * M k Ψ k + M r * M n 1 Ψ n 1 ,
I ( x , y ; z r ) = H ( x , y ) * F * ( x , y ; z r ) .
I ˜ ( ω x , ω y ; z r ) = H ˜ ( ω x , ω y ) × F ˜ * ( ω x , ω y ; z r ) ,
G ( x , y ) = { 1 x = 0 , y = 0 1 x = 1 , y = 0 0 otherwise .
E ( x , y ; z r ) = G ( x , y ) * I ( x , y ; z r ) ,
E ˜ ( ω x , ω y ; z r ) = G ˜ ( ω x , ω y ) I ˜ ( ω x , ω y ; z r ) .
E ˜ ( ω x , ω y ; z r ) = G ˜ ( ω x , ω y ) H ˜ ( ω x , ω y ) F ˜ * ( ω x , ω y ; z r ) = H ˜ ( ω x , ω y ) R ˜ ( ω x , ω y ; z r ) ,
E ( x , y ; z r ) = FT 1 { E ˜ ( ω x , ω y ; z r ) } .
if E s ( x q , y q ; d r ) = min 0 j < M { E s ( x q , y q ; d j ) } .

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