|
|
|
|
|
|
|
A primal-dual method for TV-type image denoising
|
| |
| |
|
Description: |
Total-variation (TV) image reconstruction is well accepted for denoising images with sharp edges. The main advantage of the TV-approach, which was first proposed by Rudin, Osher and Fatemi in 1992, is that edges are not smeared in the reconstructed image. Mathematically, the problem is a minimization problem with a non-differentiable functional whose efficient minimization is still a challenging issue. In this talk, a primal-dual algorithm
for TV-type image restoration is analyzed and tested. The globalized primal-dual algorithm works with generalized derivatives, converges locally at a superlinear rate and is stable
with respect to noise in the data. In addition, it utilizes a projection technique which reduces the size of the linear system that has to be solved per iteration. A comprehensive numerical
study ends the talk.
The research presented in this talk is joint work with Michael HintermÌller from the University of Graz, Austria.
Area(s):
|
|
Date: |
|
| Start Time: |
14.30 |
|
Speaker: |
Georg Stadtler (CMUC)
|
|
Place: |
Room 5.5
|
| Research Groups: |
-Numerical Analysis and Optimization
|
|
See more:
|
<Main>
|
|
| |
|
|
|
|
|
|
|
|
|
