Abstract

We present a simple and effective method for reconstructing extended focused images in digital holography using a graphics processing unit (GPU). The Fresnel transform method is simplified by an algorithm named fast Fourier transform pruning with frequency shift. Then the pixel size consistency problem is solved by coordinate transformation and combining the subpixel resampling and the fast Fourier transform pruning with frequency shift. With the assistance of the GPU, we implemented an improved parallel version of this method, which obtained about a 300–500-fold speedup compared with central processing unit codes.

© 2011 Optical Society of America

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References

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2009

2008

2005

2004

1986

K. Nagai, IEEE Trans. Acoust. Speech Signal Process. ASSP-34, 1008 (1986).
[CrossRef]

Alfieri, D.

Coppola, G.

De Nicola, S.

Ferraro, P.

Finizio, A.

Grilli, S.

Hennelly, B. M.

Javidi, B.

Matsushima, K.

McElhinney, C. P.

Memmolo, P.

Nagai, K.

K. Nagai, IEEE Trans. Acoust. Speech Signal Process. ASSP-34, 1008 (1986).
[CrossRef]

Naughton, T. J.

Paturzo, M.

Pierattini, G.

Striano, V.

Yamaguchi, I.

Yaroslavsky, L.

L. Yaroslavsky, in Advances in Signal Transforms: Theory and Application (Hindawi, 2007), pp. 337–405.

Yaroslavsky, L. P.

Zhang, F.

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Figures (4)

Fig. 1
Fig. 1

Coordinate system of the FTM.

Fig. 2
Fig. 2

Experimental setup for recording the off-axis hologram of a tilted reflective object. BS, beam splitter; MO, microscope objective; PH, pinhole; L, lens; M, mirror.

Fig. 3
Fig. 3

Reconstruction of a steel ruler by different methods. (a), (b) Images reconstructed at depths of 32.0 and 33.4 cm by FTM, respectively; (c) EFI obtained by this method.

Fig. 4
Fig. 4

Reconstruction of a USAF target by different methods. (a), (b) Images reconstructed at depths of 16.3 and 17.3 cm by FTM, respectively; (c), (d) EFIs obtained by this method.

Tables (1)

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Table 1 Comparison of Reconstruction Time Using a CPU and a GPU

Equations (2)

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U ( ξ , η ) = ( 1 / j λ d ) exp ( j 2 π d / λ ) exp [ j π ( ξ 2 + η 2 ) / ( λ d ) ] × F { I ( x , y ) R ( x , y ) exp [ j π ( x 2 + y 2 ) / ( λ d ) ] } ,
m j = a x ξ j / d j + N / 2 , n j = a y η j / d j + N / 2 ,

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