Imaging and other inverse problems are most frequently formulated using vector space-valued data. In other situations, however, a more natural formulation is obtained using manifold-valued data. Examples include problems involving shapes and interfaces, as well as problems featuring normal vector fields or diffusion tensors. In this presentation, we will give an introduction into imaging and inverse problems on manifolds and present optimality conditions, algorithms and numerical examples.
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