随机中心聚集半色调算法

目的由误差扩散半色调算法得到的二值图像存在明显的规律性纹理,针对该问题提出随机中心聚集半色调算法。方法利用蓝噪声半色调阈值矩阵算法生成随机均匀分布的种子点,采用三角网生长算法构建Delaunay三角网格,在确定三角网像素成员后,根据像素点在三角形区域内的分布位置得到该位置像素的阈值,最后通过将连续调图像与阈值矩阵的阈值比较得到半色调图像。结果同误差扩散算法相比,提出的方法可以减少半色调图像的人工纹理,图像视觉效果较好。结论文中算法可以改善半色调图像质量,实验结果证明了该方法的有效性。

Stochastically Seeded Clustered Halftone Algorithm

The work aims to propose the stochastically seeded clustered halftone algorithm with respect to the problem that the binary image obtained by error diffusion halftone algorithm has obvious structured artifacts. The stochastically seeded dots were generated by means of blue noise halftone threshold matrix algorithm. The Delaunay triangulation network was constructed with the triangulation network growth algorithm. After the pixel members of triangulation network were confirmed, based on the position of pixel points distributed in the triangular area, the threshold of pixels at such position was obtained. Finally, the halftone images were obtained after the comparison on the thresholds of continuous-tone image and the threshold matrix. Compared with the error diffusion algorithm, the proposed method could reduce the artificial texture of halftone images, so that the images had better visual effects. The proposed algorithm can improve the quality of the halftone images, and the experimental results illustrate the effectiveness of such method.