New void-and-cluster method for improved halftone uniformity

Dithering quality of the void and cluster algorithm suffers due to fixed filter width and absence of a well-defined criterion for selecting among equally likely candidates during the computation of the locations of the tightest clusters and largest voids. Various researchers have addressed the issue of fixed filter width by adaptively changing the width with experimentally determined values. This paper addresses both aforementioned issues by using a Voronoi tessellation and three criteria to select among equally likely candidates. The algorithm uses vertices of the Voronoi tessellation, and the areas of the Voronoi regions to determine the locations of the largest voids and the tightest clusters. During void and cluster operations there may be multiple equally likely candidates for the locations of the largest voids and the tightest clusters. The selection among equally-likely candidates is important when the number of candidates is larger than the number of dots for a given quantization level, or if there are candidates within the local neighborhood of one of the candidate points, or if a candidate’s Voronoi region shares one or more vertices with another candidate’s Voronoi region. Use of these methods leads to more uniform dot patterns for light and dark tones. The improved algorithm is compared with other dithering methods based on power spectrum characteristics and visual evaluation.