Approximating Poisson Disk Distributions by Means of a Stochastic Dither Array

dc.contributor.authorAlford, Jennifer R.en_US
dc.contributor.authorSheppard, David G.en_US
dc.contributor.editorJohn Collomosse and Ian Grimsteaden_US
dc.date.accessioned2014-01-31T20:11:54Z
dc.date.available2014-01-31T20:11:54Z
dc.date.issued2010en_US
dc.description.abstractAchieving blue noise point set distributions has been a common goal of two largely separate research communities: computer graphics and digital halftoning. Computer graphics research has focused largely on geometric solutions in continuous spaces. Digital halftoning research has focused on signal processing solutions in discrete imagebased space. Usage of Poisson Disk point sets in computer graphics has grown beyond sampling, including object distribution and texturing, among others. The image-based field of digital halftoning can provide additional tools for graphics researchers and practitioners. It is of interest to explore the suitability of digital halftoning technology to two classic problems in computer graphics: (1) approximating Poisson Disk point distributions of constant density and (2) importance sampling of an underlying importance function. Exemplary methods from each field are implemented and, by applying well-established measures of the radially averaged power spectrum and anisotropy plots, are shown to be quite similar, although the approaches are mathematically not equivalent. Additionally, we compare the relative radius of the point sets. Further, the ability of dither array construction techniques to shape spectral characteristics of dot patterns is shown with several variations of design parameters.en_US
dc.description.seriesinformationTheory and Practice of Computer Graphicsen_US
dc.identifier.isbn978-3-905673-75-3en_US
dc.identifier.urihttps://doi.org/10.2312/LocalChapterEvents/TPCG/TPCG10/083-090en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Picture/Image GenerationBitmap and framebuffer operations ; I.4.1 [Computer Graphics]: Image Processing and Computer VisionDigitization and Image CaptureSamplingen_US
dc.titleApproximating Poisson Disk Distributions by Means of a Stochastic Dither Arrayen_US
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