抖动
粒度
计算机科学
采样(信号处理)
卷积(计算机科学)
算法
亮度
高斯分布
噪音(视频)
人工智能
计算机图形学(图像)
计算机视觉
图像(数学)
噪声整形
物理
光学
滤波器(信号处理)
量子力学
人工神经网络
操作系统
作者
Christian Schmaltz,Pascal Gwosdek,Andrés Bruhn,Joachim Weickert
标识
DOI:10.1111/j.1467-8659.2010.01716.x
摘要
Abstract We introduce a new global approach for image dithering, stippling, screening and sampling. It is inspired by the physical principles of electrostatics. Repelling forces between equally charged particles create a homogeneous distribution in flat areas, while attracting forces from the image brightness values ensure a high approximation quality. Our model is transparent and uses only two intuitive parameters: One steers the granularity of our halftoning approach, and the other its regularity. We evaluate two versions of our algorithm: A discrete version for dithering that ties points to grid positions, as well as a continuous one which does not have this restriction, and can thus be used for stippling or sampling density functions. Our methods create very few visual artefacts, reveal favourable blue‐noise behaviour in the frequency domain, and have a lower approximation error under Gaussian convolution than state‐of‐the‐art methods.
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