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

Author

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

Author_Institution

Center for Perceptual Syst., Univ. of Texas, Austin, TX, USA

Volume

10

Issue

4

fYear

2003

fDate

4/1/2003 12:00:00 AM

Firstpage

93

Lastpage

97

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 (see IEEE Trans. Image Processing, vol.10, p.1552-65, Oct. 2001) 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, 1993), and linearized CIELab (by Flohr, Kolpatzik, Balasubramanian, Carrara, Bouman, and Allebach, 1993).

Keywords

filtering theory; image colour analysis; image resolution; spatial filters; visual perception; Euclidean distance; HVS models; color image; correlation; grayscale images; high-resolution image; human visual system; image halftoning; linear color-separable models; low-resolution image; matrix-valued coefficients; opponent color space; perceptual meaning; spatial filters; vector error diffusion halftoning; vector error filter optimization; Color; Displays; Filters; Humans; Image converters; Image processing; Matrix converters; Printing; Vectors; Visual system;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2002.806708

Filename

1186762