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基于重心Delaunay三角剖分的蓝噪声点采样算法

Blue-Noise Point Sampling Based on Centroidal Delaunay Triangulation

  • 摘要: 为了生成带有高质量蓝噪声性质的采样分布,提出一种基于重心Delaunay三角剖分的点采样算法.该算法将Delaunay三角剖分与1-邻域三角片重心相结合,迭代地将每个采样点移至其1-邻域三角片的重心处并更新采样点之间的拓扑连接关系;重心通过给定的密度函数计算得出.实验结果表明,本文算法在运行效率与鲁棒性方面均有一定优势.

     

    Abstract: We present an algorithm for generating point distributions with high-quality blue noise characteristics based on centroidal Delaunay triangulation. The method combines Delaunay triangulation with centroidal patch triangulation, and iteratively moves each vertex to the centroid of its 1-ring neighborhood and updates the topological connectivity between the sampling points. The centroid of a patch is calculated by using a given density function. The experimental results demonstrate the effectiveness and robustness of the proposed algorithm.

     

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