Linear color-separable human visual system models for vector error diffusion halftoning

Vishal Monga, Wilson S. Geisler, Brian L. Evans

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Image halftoning converts a high-resolution image to a low-resolution image, e.g., a 24-bit color image to a three-bit color image, for printing and display. Vector error diffusion captures correlation among color planes by using an error filter with matrix-valued coefficients. In optimizing vector error filters, Damera-Venkata and Evans transform the error image into an opponent color space where Euclidean distance has perceptual meaning. This letter evaluates color spaces for vector error filter optimization. In order of increasing quality, the color spaces are YIQ, YUV, opponent (by Poirson and Wandell), and linearized CIELab (by Flohr, Kolpatzik, Balasubramanian, Carrara, Bouman, and Allebach).

Original languageEnglish (US)
Pages (from-to)93-97
Number of pages5
JournalIEEE Signal Processing Letters
Volume10
Issue number4
DOIs
StatePublished - Apr 1 2003

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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