DIGITAL HALFTONING BY MEANS OF GREEN-NOISE MASKS
Daniel Leo Lau, Gonzalo R. Arce and Neal C. Gallagher

ABSTRACT: In this paper, 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 to 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 for printers with high. Being that blue-noise is a limiting case of green-noise, this new technique can even create blue-noise masks.

APPEARED: Journal of the Optical Society of America A, vol. 16, no. 7, Jul. 1999, pp. 1575-1586.

SPONSORS: This work was sponsored, in part, by the National Science Foundation under grant CDA-9703088





Dr. Daniel Leo Lau
Department of Electrical and Computer Engineering
University of Kentucky
453 Anderson Hall
Lexington, KY 40506-0046, USA
(859) 257-2300 x273
dllau@engr.uky.edu

last edited on 3/3/03