Center of Multimedia Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong.
IEEE Trans Image Process. 2010 Jul;19(7):1808-23. doi: 10.1109/TIP.2010.2044961. Epub 2010 Mar 8.
Multiscale error diffusion (MED) is superior to conventional error diffusion algorithms as it can eliminate directional hysteresis completely and possesses a good blue noise characteristic. However, due to its filter design, it is not suitable for systems with poor isolated dot generation and instable dot gain. In this paper, we propose a MED algorithm to produce halftones of desirable green noise characteristics. This algorithm allows one to adjust the desirable cluster size freely through a single parameter and supports a linear relationship between the cluster size and the input gray level. With a close-to-isotropic diffusion filter, the algorithm can effectively remove pattern artifacts, eliminate directional artifacts and preserve original image details. Analysis and simulation results show that it provides better performance in terms of various aspects including dot distribution, anisotropy and output image quality as compared with other conventional green noise error diffusion algorithms.
多尺度误差扩散(MED)优于传统的误差扩散算法,因为它可以完全消除方向滞后,并且具有良好的蓝噪声特性。然而,由于其滤波器设计,它不适用于孤立点生成不良和网点增益不稳定的系统。在本文中,我们提出了一种 MED 算法,用于产生具有理想绿噪声特性的半色调。该算法允许通过单个参数自由调整所需的簇大小,并支持簇大小与输入灰度级之间的线性关系。使用接近各向同性的扩散滤波器,该算法可以有效地去除图案伪影,消除方向伪影并保留原始图像细节。分析和仿真结果表明,与其他传统的绿噪声误差扩散算法相比,它在网点分布、各向异性和输出图像质量等方面具有更好的性能。