Efficient block-wise algorithm for ompressive holography

Hua Zhang; Liangcai Cao; Hao Zhang; Wenhui Zhang; Guofan Jin; David J. Brady

doi:10.1364/OE.25.024991

Efficient block-wise algorithm for ompressive holography

Hua Zhang, Liangcai Cao, Hao Zhang, Wenhui Zhang, Guofan Jin, David J. Brady

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

Compressive holography is a relatively time-consuming image estimation in convex optimized problem. We propose an efficient block-wise algorithm to limit the searching space and reduce the calculation time while keeping the reconstruction quality. The effective anti-aliasing boundary of the sub-hologram is located to determine the block size for compressive reconstruction in the total-variation two-step iterative shrinkage/thresholding algorithm. Padded sub-holograms could be reconstructed in parallel by using multi-core processors. Compared with the traditional compressive holography, the block-wise algorithm could take approximately 1/50 of the reconstruction time and achieve an improved reconstruction quality.

Original language	English (US)
Pages (from-to)	24991-25003
Number of pages	13
Journal	Optics Express
Volume	25
Issue number	21
DOIs	https://doi.org/10.1364/OE.25.024991
State	Published - Oct 16 2017
Externally published	Yes

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics

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10.1364/OE.25.024991

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abstract = "Compressive holography is a relatively time-consuming image estimation in convex optimized problem. We propose an efficient block-wise algorithm to limit the searching space and reduce the calculation time while keeping the reconstruction quality. The effective anti-aliasing boundary of the sub-hologram is located to determine the block size for compressive reconstruction in the total-variation two-step iterative shrinkage/thresholding algorithm. Padded sub-holograms could be reconstructed in parallel by using multi-core processors. Compared with the traditional compressive holography, the block-wise algorithm could take approximately 1/50 of the reconstruction time and achieve an improved reconstruction quality.",

author = "Hua Zhang and Liangcai Cao and Hao Zhang and Wenhui Zhang and Guofan Jin and Brady, {David J.}",

note = "Funding Information: Innovation Method Fund of China (2015IM020500); National Natural Science Foundation of China (NSFC) (61775117, 61327902, 61505095); National Instrument Program (2012YQ 140005); National Basic Research Program of China (2013CB328803). Publisher Copyright: {\textcopyright} 2017 Optical Society of America.",

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T1 - Efficient block-wise algorithm for ompressive holography

AU - Zhang, Hua

AU - Cao, Liangcai

AU - Zhang, Hao

AU - Zhang, Wenhui

AU - Jin, Guofan

AU - Brady, David J.

N1 - Funding Information: Innovation Method Fund of China (2015IM020500); National Natural Science Foundation of China (NSFC) (61775117, 61327902, 61505095); National Instrument Program (2012YQ 140005); National Basic Research Program of China (2013CB328803). Publisher Copyright: © 2017 Optical Society of America.

PY - 2017/10/16

Y1 - 2017/10/16

N2 - Compressive holography is a relatively time-consuming image estimation in convex optimized problem. We propose an efficient block-wise algorithm to limit the searching space and reduce the calculation time while keeping the reconstruction quality. The effective anti-aliasing boundary of the sub-hologram is located to determine the block size for compressive reconstruction in the total-variation two-step iterative shrinkage/thresholding algorithm. Padded sub-holograms could be reconstructed in parallel by using multi-core processors. Compared with the traditional compressive holography, the block-wise algorithm could take approximately 1/50 of the reconstruction time and achieve an improved reconstruction quality.

AB - Compressive holography is a relatively time-consuming image estimation in convex optimized problem. We propose an efficient block-wise algorithm to limit the searching space and reduce the calculation time while keeping the reconstruction quality. The effective anti-aliasing boundary of the sub-hologram is located to determine the block size for compressive reconstruction in the total-variation two-step iterative shrinkage/thresholding algorithm. Padded sub-holograms could be reconstructed in parallel by using multi-core processors. Compared with the traditional compressive holography, the block-wise algorithm could take approximately 1/50 of the reconstruction time and achieve an improved reconstruction quality.

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Efficient block-wise algorithm for ompressive holography

Abstract

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