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Parallel structure-aware halftoning

delete2012-03-08
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PRE
AI
H
Huisi Wu *
T
Tien‐Tsin Wong
P
Pheng‐Ann Heng
DOI:10.1007/s11042-012-1048-6delete
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Abstract

Abstract

En 中文
Structure-aware halftoning technique is one of the state-of-the-art algorithms for generating structure-preserving bitonal images. However, the slow optimization process prohibits its real-time application. This is due to its high computational cost of similarity measurement and iterative refinement. Unfortunately, the structure-aware halftoning cannot be straightforwardly parallelized due to its data dependency nature. In this paper, we propose a parallel algorithm to boost the optimization of the structure-aware halftoning. Our main idea is to exploit the spatial independence during the evaluation of the objective function and temporal independence among the iterations. Specifically, we introduce a parallel Poisson-disk algorithm during the selection of pixel swaps, which guarantees the independency between parallel processes. Graphics processing unit (GPU) implementation of the technique leads to a significant speedup without sacrificing the quality. Our experiments demonstrate the effectiveness of the proposed parallel algorithm in generating structure-preserving bitonal images with much less time, especially for large images.
Keywords:
Digital halftoning
GPU
SSIM
Parallel poisson-disk sampling
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Multimedia Tools and Applications cover
Multimedia Tools and Applications
IF:
3
Papers:
2.0W
Citations:
3.2W

Organization

C
Chinese University of Hong Kong
Scholars:
3.4W
Papers: 3.2W
Citations: 5.6W
S
shenzhen university
Scholars:
4.6W
Papers: 3.4W
Citations: 72
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