Algorithms for solid noise synthesis
Algorithms for solid noise synthesis
复制标题
固体噪声合成算法
DOI：
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发表时间：
1989
期刊：
影响因子：
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通讯作者：
J. P. Lewis
中科院分区：
文献类型：
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作者：
J. P. Lewis
固体噪声是定义空间中每个点的随机值的函数。固体噪声在表面纹理、随机建模和自然现象动画方面具有直接而强大的应用。对现有的固体噪声合成算法进行了调查，并提出了两种新算法。第一个使用维纳插值在离散晶格上插值随机值。第二个是高效的稀疏卷积算法。这两种算法都是为模型引导合成而开发的，其中噪声的采样和构造仅发生在需要噪声值的点，而不是在定期采样的空间区域。本文试图阐述选择这些特定算法的基本原理。新算法具有效率高、改进对噪声功率谱的控制以及不存在伪影的优点。卷积算法还允许以质量换取效率，而不会引入明显的确定性效应。该算法特别适合需要高质量固体噪声的应用。显示了随机建模和实体纹理中的几个示例应用程序。
A solid noise is a function that defines a random value at each point in space. Solid noises have immediate and powerful applications in surface texturing, stochastic modeling, and the animation of natural phenomena.Existing solid noise synthesis algorithms are surveyed and two new algorithms are presented. The first uses Wiener interpolation to interpolate random values on a discrete lattice. The second is an efficient sparse convolution algorithm. Both algorithms are developed for model-directed synthesis, in which sampling and construction of the noise occur only at points where the noise value is required, rather than over a regularly sampled region of space. The paper attempts to present the rationale for the selection of these particular algorithms.The new algorithms have advantages of efficiency, improved control over the noise power spectrum, and the absence of artifacts. The convolution algorithm additionally allows quality to be traded for efficiency without introducing obvious deterministic effects. The algorithms are particularly suitable for applications where high-quality solid noises are required. Several sample applications in stochastic modeling and solid texturing are shown.