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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.
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