maximize


@article{ClDiRu04,
  author = {Clarenz, U. and Diewald, U. and Rumpf, M.},
  title = {Processing Textured Surfaces via Anisotropic Geometric Diffusion},
  journal = {IEEE Transactions on Image Processing},
  year = {2004},
  volume = {13},
  pages = {248--261},
  number = {2},
  abstract = {A multiscale method in surface processing is presented which carries
	over image processing methodology based on nonlinear diffusion equations
	to the fairing of noisy, textured, parametric surfaces. The aim is
	to smooth noisy, triangulated surfaces and accompanying noisy textures
	- as they are delivered by new scanning technology - while enhancing
	geometric and texture features. For an initial textured surface a
	fairing method is described which simultaneously processes the texture
	and the surface. Considering an appropriate coupling of the two smoothing
	processes one can take advantage of the frequently present strong
	correlation between edge features in the texture and on the surface
	edges. The method is based on an anisotropic curvature evolution
	of the surface itself and an anisotropic diffusion on the processed
	surface applied to the texture. Here, the involved diffusion tensors
	depends on a regularized shape operator of the evolving surface and
	on regularized texture gradients. A spatial finite element discretization
	on arbitrary unstructured triangular grids and a semi-implicit finite
	difference discretization in time are the building blocks of the
	corresponding numerical algorithm. A normal projection is applied
	to the discrete propagation velocity to avoid tangential drifting
	in the surface evolution. Different applications underline the efficiency
	and flexibility of the presented surface processing tool.},
  pdf = {http://numod.ins.uni-bonn.de/research/papers/public/ClDiRu04.pdf 1}
}