Quadrature Nodes Meet Stippling Dots

  • Manuel Gräf
  • Daniel Potts
  • Gabriele Steidl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6667)

Abstract

The stippling technique places black dots such that their density gives the impression of tone. This is the first paper that relates the distribution of stippling dots to the classical mathematical question of finding ’optimal’ nodes for quadrature rules. More precisely, we consider quadrature error functionals on reproducing kernel Hilbert spaces (RKHSs) with respect to the quadrature nodes and suggest to use optimal distributions of these nodes as stippling dot positions. Interestingly, in special cases, our quadrature errors coincide with discrepancy functionals and with recently proposed attraction-repulsion functionals. Our framework enables us to consider point distributions not only in ℝ2 but also on the torus \({\mathbb{T}}^2\) and the sphere \({\mathbb{S}}^2\). For a large number of dots the computation of their distribution is a serious challenge and requires fast algorithms. To this end, we work in RKHSs of bandlimited functions, where the quadrature error can be replaced by a least squares functional. We apply a nonlinear conjugate gradient (CG) method on manifolds to compute a minimizer of this functional and show that each step can be efficiently realized by nonequispaced fast Fourier transforms. We present numerical stippling results on \({\mathbb{S}}^2\).

Keywords

Manifold 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Manuel Gräf
    • 1
  • Daniel Potts
    • 1
  • Gabriele Steidl
    • 2
  1. 1.Faculty of MathematicsChemnitz University of TechnologyGermany
  2. 2.Department of MathematicsUniversity of KaiserslauternGermany

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