Discrepancy-based digital halftoning: Automatic evaluation and optimization

Kunihiko Sadakane, Nadia Takki Chebihi, Takeshi Tokuyama

Research output: Chapter in Book/Report/Conference proceedingChapter

5 Citations (Scopus)

Abstract

Digital halftoning is a problem of computing a binary image approximating an input gray (or color) image. We consider two problems on digital halftoning: mathematical evaluation of a halftoning image and design of optimization-based halftoning algorithms. We propose an efficient automatic evaluation system of halftoning images by using quality evaluation functions based on discrepancy measures. Our experimental results on the evaluation system infer that the discrepancy corresponding to a regional error is a good evaluation measurement, and thus we design algorithms to reduce this discrepancy measure.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsTetsuo Asano, Reinhard Klette, Chrisitan Ronse
PublisherSpringer Verlag
Pages301-319
Number of pages19
ISBN (Electronic)3540009167, 9783540009160
DOIs
Publication statusPublished - 2003
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2616
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Digital halftoning
  • Discrepancy
  • Quality evaluation
  • Rounding

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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