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CLC number: TP391

On-line Access: 2013-12-06

Received: 2013-05-22

Revision Accepted: 2013-10-18

Crosschecked: 2013-11-18

Cited: 1

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Journal of Zhejiang University SCIENCE C 2013 Vol.14 No.12 P.918-929


An improved parallel contrast-aware halftoning

Author(s):  Ling-yue Liu, Wei Chen, Tien-tsin Wong, Wen-ting Zheng, Wei-dong Geng

Affiliation(s):  State Key Lab of CAD & CG, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   liulingyue@zju.edu.cn, wtzheng@cad.zju.edu.cn

Key Words:  Digital image halftoning, Error diffusion, GPU, Quantization, Space-filling curve

Ling-yue Liu, Wei Chen, Tien-tsin Wong, Wen-ting Zheng, Wei-dong Geng. An improved parallel contrast-aware halftoning[J]. Journal of Zhejiang University Science C, 2013, 14(12): 918-929.

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%A Wei Chen
%A Tien-tsin Wong
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T1 - An improved parallel contrast-aware halftoning
A1 - Ling-yue Liu
A1 - Wei Chen
A1 - Tien-tsin Wong
A1 - Wen-ting Zheng
A1 - Wei-dong Geng
J0 - Journal of Zhejiang University Science C
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EP - 929
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1300142

digital image halftoning is a widely used technique. However, achieving high fidelity tone reproduction and structural preservation with low computational time cost remains a challenging problem. This paper presents a highly parallel algorithm to boost real-time application of serial structure-preserving error diffusion. The contrast-aware halftoning approach is one such technique with superior structure preservation, but it offers only a limited opportunity for graphics processing unit (GPU) acceleration. Our method integrates contrast-aware halftoning into a new parallelizable error-diffusion halftoning framework. To eliminate visually disturbing artifacts resulting from parallelization, we propose a novel multiple quantization model and space-filling curve to maintain tone consistency, blue-noise property, and structure consistency. Our GPU implementation on a commodity personal computer achieves a real-time performance for a moderately sized image. We demonstrate the high quality and performance of the proposed approach with a variety of examples, and provide comparisons with state-of-the-art methods.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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