A simple push-pull algorithm for blue-noise sampling

Abdalla G.M. Ahmed, Jianwei Guo, Dong Ming Yan*, Jean Yves Franceschia, Xiaopeng Zhang, Oliver Deussen

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    39 Scopus citations

    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 languageEnglish (US)
    Article number7790842
    Pages (from-to)2496-2508
    Number of pages13
    JournalIEEE Transactions on Visualization and Computer Graphics
    Volume23
    Issue number12
    DOIs
    StatePublished - Dec 1 2017

    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

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