Digital Halftoning through Approximate Optimization of Scale-Related Perceived Error Metric

Zifen HE; Yinhui ZHANG

doi:10.1587/transinf.2015EDL8156

Digital Halftoning through Approximate Optimization of Scale-Related Perceived Error Metric

Zifen HE, Yinhui ZHANG

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This work presents an approximate global optimization method for image halftone by fusing multi-scale information of the tree model. We employ Gaussian mixture model and hidden Markov tree to characterized the intra-scale clustering and inter-scale persistence properties of the detailed coefficients, respectively. The model of multiscale perceived error metric and the theory of scale-related perceived error metric are used to fuse the statistical distribution of the error metric of the scale of clustering and cross-scale persistence. An Energy function is then generated. Through energy minimization via graph cuts, we gain the halftone image. In the related experiment, we demonstrate the superior performance of this new algorithm when compared with several algorithms and quantitative evaluation.

Publication: IEICE TRANSACTIONS on Information Vol.E99-D No.1 pp.305-308

Publication Date: 2016/01/01

Publicized: 2015/10/20

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2015EDL8156

Type of Manuscript: LETTER

Category: Image Processing and Video Processing

Authors

Zifen HE
Kunming University of Science and Technology
Yinhui ZHANG
Kunming University of Science and Technology

Keyword

halftoning, approximate global optimization, multiscale error metric, scale-related

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Zifen HE, Yinhui ZHANG, "Digital Halftoning through Approximate Optimization of Scale-Related Perceived Error Metric" in IEICE TRANSACTIONS on Information, vol. E99-D, no. 1, pp. 305-308, January 2016, doi: 10.1587/transinf.2015EDL8156.
Abstract: This work presents an approximate global optimization method for image halftone by fusing multi-scale information of the tree model. We employ Gaussian mixture model and hidden Markov tree to characterized the intra-scale clustering and inter-scale persistence properties of the detailed coefficients, respectively. The model of multiscale perceived error metric and the theory of scale-related perceived error metric are used to fuse the statistical distribution of the error metric of the scale of clustering and cross-scale persistence. An Energy function is then generated. Through energy minimization via graph cuts, we gain the halftone image. In the related experiment, we demonstrate the superior performance of this new algorithm when compared with several algorithms and quantitative evaluation.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.2015EDL8156/_p

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@ARTICLE{e99-d_1_305,
author={Zifen HE, Yinhui ZHANG, },
journal={IEICE TRANSACTIONS on Information},
title={Digital Halftoning through Approximate Optimization of Scale-Related Perceived Error Metric},
year={2016},
volume={E99-D},
number={1},
pages={305-308},
abstract={This work presents an approximate global optimization method for image halftone by fusing multi-scale information of the tree model. We employ Gaussian mixture model and hidden Markov tree to characterized the intra-scale clustering and inter-scale persistence properties of the detailed coefficients, respectively. The model of multiscale perceived error metric and the theory of scale-related perceived error metric are used to fuse the statistical distribution of the error metric of the scale of clustering and cross-scale persistence. An Energy function is then generated. Through energy minimization via graph cuts, we gain the halftone image. In the related experiment, we demonstrate the superior performance of this new algorithm when compared with several algorithms and quantitative evaluation.},
keywords={},
doi={10.1587/transinf.2015EDL8156},
ISSN={1745-1361},
month={January},}

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TY - JOUR
TI - Digital Halftoning through Approximate Optimization of Scale-Related Perceived Error Metric
T2 - IEICE TRANSACTIONS on Information
SP - 305
EP - 308
AU - Zifen HE
AU - Yinhui ZHANG
PY - 2016
DO - 10.1587/transinf.2015EDL8156
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2016
AB - This work presents an approximate global optimization method for image halftone by fusing multi-scale information of the tree model. We employ Gaussian mixture model and hidden Markov tree to characterized the intra-scale clustering and inter-scale persistence properties of the detailed coefficients, respectively. The model of multiscale perceived error metric and the theory of scale-related perceived error metric are used to fuse the statistical distribution of the error metric of the scale of clustering and cross-scale persistence. An Energy function is then generated. Through energy minimization via graph cuts, we gain the halftone image. In the related experiment, we demonstrate the superior performance of this new algorithm when compared with several algorithms and quantitative evaluation.
ER -