Monga Vishal, Damera-Venkata Niranjan, Evans Brian L
Xerox Wilson Research Center, Webster, NY 14580, USA.
IEEE Trans Image Process. 2007 Jan;16(1):198-211. doi: 10.1109/tip.2006.884923.
Grayscale error diffusion introduces nonlinear distortion (directional artifacts and false textures), linear distortion (sharpening), and additive noise. Tone-dependent error diffusion (TDED) reduces these artifacts by controlling the diffusion of quantization errors based on the input graylevel. We present an extension of TDED to color. In color-error diffusion, which color to render becomes a major concern in addition to finding optimal dot patterns. We propose a visually meaningful scheme to train input-level (or tone-) dependent color-error filters. Our design approach employs a Neugebauer printer model and a color human visual system model that takes into account spatial considerations in color reproduction. The resulting halftones overcome several traditional error-diffusion artifacts and achieve significantly greater accuracy in color rendition.
灰度误差扩散会引入非线性失真(方向性伪影和虚假纹理)、线性失真(锐化)以及加性噪声。色调相关误差扩散(TDED)通过基于输入灰度级控制量化误差的扩散来减少这些伪影。我们提出了TDED在彩色领域的扩展。在彩色误差扩散中,除了寻找最佳网点图案外,渲染哪种颜色也成为一个主要问题。我们提出了一种视觉上有意义的方案来训练与输入级别(或色调)相关的彩色误差滤波器。我们的设计方法采用了纽格鲍尔打印机模型和考虑了色彩再现中空间因素的彩色人类视觉系统模型。由此产生的半色调图像克服了几种传统误差扩散伪影,并在色彩再现方面实现了显著更高的精度。