maximize


@article{PrRu00,
  author = {Preu{\ss}er, T. and Rumpf, M.},
  title = {An Adaptive Finite Element Method for Large Scale Image Processing},
  journal = {Journal of Visual Communication and Image Representation},
  year = {2000},
  volume = {11},
  pages = {183--195},
  number = {2},
  abstract = {Nonlinear diffusion methods have proved to be powerful methods in
	the processing of 2D and 3D images. They allow a denoising and smoothing
	of image intensities while retaining and enhancing edges. As time
	evolves in the corresponding process, a scale of successively coarser
	image details is generated. Certain features, however, remain highly
	resolved and sharp. On the other hand, compression is an important
	topic in image processing as well. Here a method is presented which
	combines the two aspects in an efficient way. It is based on a semi--implicit
	Finite Element implementation of nonlinear diffusion. Error indicators
	guide a successive coarsening process. This leads to locally coarse
	grids in areas of resulting smooth image intensity, while enhanced
	edges are still resolved on fine grid levels. Special emphasis has
	been put on algorithmical aspects such as storage requirements and
	efficiency. Furthermore, a new nonlinear anisotropic diffusion method
	for vector field visualization is presented.},
  doi = {10.1006/jvci.1999.0444},
  pdf = {http://numod.ins.uni-bonn.de/research/papers/public/PrRu00.pdf 1},
  html = {http://numerik.math.uni-duisburg.de/research/research-sites/preusser/LargeScaleFE/index.html}
}