A Simple Push-Pull Algorithm for Blue-Noise Sampling
A Simple Push-Pull Algorithm for Blue-Noise Sampling
复制标题
一种简单的蓝噪声采样推挽算法
DOI：
10.1109/tvcg.2016.2641963
复制
发表时间：
2017-12-01
影响因子：
5.2
通讯作者：
Deussen, Oliver
中科院分区：
文献类型：
--
作者：
Ahmed, Abdalla G. M.;Guo, Jianwei;Deussen, Oliver
我们描述了一种简单的推拉优化（PPO）算法，通过对给定点集实施空间约束来进行蓝噪声采样。约束可以是样本之间的最小距离、任意点与最近样本之间的最大距离以及样本容量（Voronoi 单元的面积）与平均容量的最大偏差。所有这些约束都基于 Delaunay 三角剖分中出现的拓扑，并且可以将它们组合起来以提高采样质量和效率。此外，我们的算法为不同目标（例如噪声和混叠）之间的权衡提供了灵活性。我们展示了所提出算法的几种应用，包括抗锯齿、点画和非钝角重新网格化。我们的实验结果说明了所提出方法的效率和鲁棒性。此外，我们证明我们的重新网格化质量优于当前最先进的方法。
We describe a simple push-pull optimization (PPO) algorithm for blue-noise sampling by enforcing spatial constraints on given point sets. Constraints can be a minimum distance between samples, a maximum distance between an arbitrary point and the nearest sample, and a maximum deviation of a sample's capacity (area of Voronoi cell) from the mean capacity. All of these constraints are based on the topology emerging from Delaunay triangulation, and they can be combined for improved sampling quality and efficiency. In addition, our algorithm offers flexibility for trading-off between different targets, such as noise and aliasing. We present several applications of the proposed algorithm, including anti-aliasing, stippling, and non-obtuse remeshing. Our experimental results illustrate the efficiency and the robustness of the proposed approach. Moreover, we demonstrate that our remeshing quality is superior to the current state-of-the-art approaches.