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Volumetric Nonlinear Anisotropic Diffusion on GPUs

  • Andreas Schwarzkopf
  • Thomas Kalbe
  • Chandrajit Bajaj
  • Arjan Kuijper
  • Michael Goesele
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6667)

Abstract

We present an efficient implementation of volumetric nonlinear anisotropic image diffusion on modern programmable graphics processing units (GPUs). We avoid the computational bottleneck of a time consuming eigenvalue decomposition in ℝ3. Instead, we use a projection of the Hessian matrix along the surface normal onto the tangent plane of the local isodensity surface and solve for the remaining two tangent space eigenvectors. We derive closed formulas to achieve this resulting in efficient GPU code. We show that our most complex volumetric nonlinear anisotropic diffusion gains a speed up of more than 600 compared to a CPU solution.

Keywords

Tangent Space Diffusion Tensor Tangent Plane Anisotropic Diffusion Closed Formula 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Andreas Schwarzkopf
    • 1
  • Thomas Kalbe
    • 1
  • Chandrajit Bajaj
    • 2
  • Arjan Kuijper
    • 1
    • 3
  • Michael Goesele
    • 1
  1. 1.Technische Universität DarmstadtGermany
  2. 2.ICES-CVC University of Texas at AustinUSA
  3. 3.Fraunhofer IGDDarmstadtGermany

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