Green noise digital halftoning with multiscale error diffusion

Yik Hing Fung, Yuk Hee Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

17 Citations (Scopus)

Abstract

Multiscale error diffusion (MED) is superior to conventional error diffusion algorithms as it can eliminate directional hysteresis completely and possesses a good blue noise characteristic. However, due to its filter design, it is not suitable for systems with poor isolated dot generation and instable dot gain. In this paper, we propose a MED algorithm to produce halftones of desirable green noise characteristics. This algorithm allows one to adjust the desirable cluster size freely through a single parameter and supports a linear relationship between the cluster size and the input gray level. With a close-to-isotropic diffusion filter, the algorithm can effectively remove pattern artifacts, eliminate directional artifacts and preserve original image details. Analysis and simulation results show that it provides better performance in terms of various aspects including dot distribution, anisotropy and output image quality as compared with other conventional green noise error diffusion algorithms.
Original languageEnglish
Article number5427084
Pages (from-to)1808-1823
Number of pages16
JournalIEEE Transactions on Image Processing
Volume19
Issue number7
DOIs
Publication statusPublished - 1 Jul 2010

Keywords

  • Error diffusion
  • Green noise
  • Halftoning
  • Multiscale error diffusion (MED)
  • Multiscale processing
  • Printing

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software

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