Anisotropic Total Variation Filtering |
| |
Authors: | Markus Grasmair Frank Lenzen |
| |
Institution: | 1. Computational Science Center, University of Vienna, Vienna, Austria 2. Heidelberg Collaboratory for Image Processing, University of Heidelberg, Heidelberg, Germany
|
| |
Abstract: | Total variation regularization and anisotropic filtering have been established as standard methods for image denoising because
of their ability to detect and keep prominent edges in the data. Both methods, however, introduce artifacts: In the case of
anisotropic filtering, the preservation of edges comes at the cost of the creation of additional structures out of noise;
total variation regularization, on the other hand, suffers from the stair-casing effect, which leads to gradual contrast changes
in homogeneous objects, especially near curved edges and corners. In order to circumvent these drawbacks, we propose to combine
the two regularization techniques. To that end we replace the isotropic TV semi-norm by an anisotropic term that mirrors the
directional structure of either the noisy original data or the smoothed image. We provide a detailed existence theory for
our regularization method by using the concept of relaxation. The numerical examples concluding the paper show that the proposed
introduction of an anisotropy to TV regularization indeed leads to improved denoising: the stair-casing effect is reduced
while at the same time the creation of artifacts is suppressed. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|