Digital halftoning by means of green-noise masks

Daniel L. Lau, Gonzalo R. Arce, Neal C. Gallagher

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

We introduce a novel technique for generating green-noise halftones—stochastic dither patterns composed of homogeneously distributed pixel clusters. Although techniques employing error diffusion have been proposed previously, the technique here employs a dither array referred to as a green-noise mask, which greatly reduces the computational complexity formerly associated with green noise. Compared with those generated with blue-noise masks, halftones generated with green-noise masks are less susceptible to printer distortions. Because green noise constitutes patterns with widely varying cluster sizes and shapes, the technique introduced here for constructing these green-noise masks is tunable; that is, it allows for specific printer traits, with small clusters reserved for printers with low distortion and large clusters reserved for printers with high distortion. Given that blue noise is a limiting case of green noise, this new technique can even create blue-noise masks.

Original languageEnglish
Pages (from-to)1575-1586
Number of pages12
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume16
Issue number7
DOIs
StatePublished - Jul 1999

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Computer Vision and Pattern Recognition

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