Abstract
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.
Original language | English (US) |
---|---|
Article number | 7790842 |
Pages (from-to) | 2496-2508 |
Number of pages | 13 |
Journal | IEEE Transactions on Visualization and Computer Graphics |
Volume | 23 |
Issue number | 12 |
DOIs | |
State | Published - Dec 1 2017 |
Bibliographical note
Funding Information:We would like to thank Zhonggui Chen, Fernando de Goes, Raanan Fattal, Mohamed S. Ebeida and Daniel Heck for providing the data and executables, Liyi Wei and Rui Wang for sharing the DDA tool. This project was supported by the Deutsche Forschungsgemeinschaft Grant (DE-620/22-1), the National Natural Science Foundation of China (61372168, 61620106003, and 61331018), the National Foreign 1000 Plan (WQ201344000169) and the Leading Talents of Guangdong Program (00201509). Dong-Ming Yan is the corresponding author. Abdalla G. M. Ahmed and Jianwei Guo are joint first authors.
Publisher Copyright:
© 1995-2012 IEEE.
Keywords
- Blue-noise sampling
- Push-pull
- Remeshing
- Stippling
- Surface sampling
ASJC Scopus subject areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Computer Graphics and Computer-Aided Design