Abstract
In this paper, we propose a method for halftoning color images based on an error diffusion technique, a color design criterion and Neugebauer models for expressing colors. For a natural extension of the conventional method for grayscale error diffusion to its color version, we first reformulate grayscale error diffusion with a one-dimensional Neugebauer model. Then we increase the dimension of the model to derive a color error diffusion method based on a three-dimensional Neugebauer model in RGB (red, green and blue) color space. Moreover, we propose a sparse Neugebauer model based on a color design criterion, or the minimal brightness variation criterion (MBVC), from which we derive a sparse Neugebauer model-based error diffusion method. Experimental results show that color halftone images produced by the proposed methods preserve the color contents in original continuous-tone images better than that by conventional color error diffusion methods. We also demonstrate that the proposed sparse method reduce halftone noise better than the state-of-the-art method based on MBVC.
Highlights
Digital halftoning is the process of converting a continuous-tone image into a pattern of a limited number of gray levels or colors
Based on the grayscale Neugebauer model in Equation (4), we propose another expression of grayscale error diffusion as follows: A pixel value hijF in H F is given by selecting black or white which has larger probability than another as hijF = arg max n x ∈{K,W }
We proposed a method for color error diffusion by extending the grayscale Neugebauer model to its color version
Summary
Digital halftoning is the process of converting a continuous-tone image into a pattern of a limited number of gray levels or colors. We show the equivalence between conventional grayscale error diffusion and the Neugebauer model-based method. Neugebauer model-based error diffusion method to its color version by extending the dimension of color space from 1D to 3D. The proposed color error diffusion method can be expected as a good candidate for the color extensions of a standard grayscale error diffusion technique. Experimental results show the effectiveness of the proposed color error diffusion method on real image data including standard images for image processing researches. The rest of this paper is organized as follows: Section 2 summarizes grayscale error diffusion, and shows the equivalence between conventional grayscale error diffusion and Neugebauer model-based method.
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