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Volumetric nonlinear anisotropic diffusion on GPUs

: Schwarzkopf, Andreas; Kalbe, Thomas; Bajaj, Chandrajit L.; Kuijper, Arjan; Goesele, Michael


Bruckstein, A.M.:
Scale space and variational methods in computer vision. Third international conference SSVM 2011. Revised selected papers : Ein-Gedi, Israel, May 29 - June 2, 2011
Berlin: Springer, 2012 (Lecture Notes in Computer Science 6667)
ISBN: 978-3-642-24784-2
ISBN: 3-642-24784-9
ISSN: 0302-9743
International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) <3, 2011, Ein-Gedi/Israel>
Fraunhofer IGD ()
partial differential equation; 3D data representation; 3D Graphics; 3D image acquisition; 3D image processing; smoothing; scale space; Forschungsgruppe Capturing Reality (CARE)

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.