@INPROCEEDINGS{DiRu00,
author = {Diewald, U. and Rumpf, M.},
title = {Visualization of Principal Curvature Directions by Anisotropic Diffusion},
booktitle = {Vision, Modeling and Visualization},
year = {2000},
editor = {Girod, B. and Greiner, G. and Niemann, H. and Seidel, H.-P.},
pages = {293--301},
abstract = {Anisotropic diffusion is known to be a powerful tool in image processing.
It enables the smoothing of initially noisy images while still retaining,
respectively sharpening edges and enhancing features. Here recent
results in the context of vector field visualization are expanded
to non Euclidean domains. The aim is to graphically represent vector
field data on two dimensional surfaces in an intuitively understandable
way. Furthermore the multiscale properties of the approach support
a scale of resolutions, ranging from detailed flow representation
to a coarse overview of field data. Here an initial noisy image intensity
is smoothed along integral lines, whereas the image is mainly sharpened
in the orthogonal direction. The method is based on a continuous
model and requires the solution of a parabolic PDE problem on manifolds.
It is discretized by finite elements on surface triangulations only
in the final implementational step. Applications are shown for principal
directions of curvature on general surfaces.},
pdf = {http://numod.ins.uni-bonn.de/research/papers/public/DiRu00.pdf}
}