{"title":"Spherical Blue Noise","authors":"Kin-Ming Wong, T. Wong","doi":"10.2312/pg.20181267","DOIUrl":null,"url":null,"abstract":"We present a physically based method which generates unstructured uniform point set directly on the S2-sphere. Spherical uniform point sets are useful for illumination sampling in Quasi Monte Carlo (QMC) rendering but it is challenging to generate high quality uniform point sets directly. Most methods rely on mapping the low discrepancy unit square point sets to the spherical domain. However, these transformed point sets often exhibit sub-optimal uniformity due to the inability of preserving the low discrepancy properties. Our method is designed specifically for direct generation of uniform point sets in the spherical domain. We name our generated result as Spherical Blue Noise point set because it shares similar point distribution characteristics with the 2D blue noise. Our point sets possess high spatial uniformity without a global structure, and we show that they deliver competitive results for illumination integration in QMC rendering, and general numerical integration on the spherical domain. CCS Concepts •Computing methodologies → Ray tracing;","PeriodicalId":88304,"journal":{"name":"Proceedings. Pacific Conference on Computer Graphics and Applications","volume":"3 1","pages":"5-8"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. Pacific Conference on Computer Graphics and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/pg.20181267","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We present a physically based method which generates unstructured uniform point set directly on the S2-sphere. Spherical uniform point sets are useful for illumination sampling in Quasi Monte Carlo (QMC) rendering but it is challenging to generate high quality uniform point sets directly. Most methods rely on mapping the low discrepancy unit square point sets to the spherical domain. However, these transformed point sets often exhibit sub-optimal uniformity due to the inability of preserving the low discrepancy properties. Our method is designed specifically for direct generation of uniform point sets in the spherical domain. We name our generated result as Spherical Blue Noise point set because it shares similar point distribution characteristics with the 2D blue noise. Our point sets possess high spatial uniformity without a global structure, and we show that they deliver competitive results for illumination integration in QMC rendering, and general numerical integration on the spherical domain. CCS Concepts •Computing methodologies → Ray tracing;
提出了一种在s2球上直接生成非结构化均匀点集的物理方法。球面均匀点集是准蒙特卡罗(Quasi Monte Carlo, QMC)渲染中照明采样的有效方法,但直接生成高质量的均匀点集具有一定的挑战性。大多数方法依赖于将低差异单位正方形点集映射到球面域。然而,这些变换后的点集往往表现出次优均匀性,因为不能保持低差异的性质。我们的方法是专门为在球面上直接生成均匀点集而设计的。我们将生成的结果命名为球形蓝噪声点集,因为它与二维蓝噪声具有相似的点分布特征。我们的点集在没有全局结构的情况下具有高空间均匀性,并且我们表明它们在QMC渲染中的照明集成以及球面上的一般数值集成方面提供了具有竞争力的结果。CCS概念•计算方法→光线追踪;