Total variation regularization for manifold-valued data

  title={Total variation regularization for manifold-valued data},
  author={Andreas Weinmann and Laurent Demaret and Martin Storath},
  journal={SIAM J. Imaging Sciences},
We consider total variation (TV) minimization for manifold-valued data. We propose a cyclic proximal point algorithm and a parallel proximal point algorithm to minimize TV functionals with -type data terms in the manifold case. These algorithms are based on iterative geodesic averaging which makes them easily applicable to a large class of data manifolds. As an application, we consider denoising images which take their values in a manifold. We apply our algorithms to diffusion tensor images and… CONTINUE READING


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