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Wavelet sparse regularization for manifold-valued data.
Multiscale Model. Simul. 18, 674-706 (2020)
n this paper, we consider the sparse regularization of manifold-valued data with respect to an interpolatory wavelet/multiscale transform. We propose and study variational models for this task and provide results on their well-posedness. We present algorithms for a numerical realization of these models in the manifold setup. Further, we provide experimental results to show the potential of the proposed schemes for applications.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Denoising ; Interpolatory Multiscale Transforms ; Interpolatory Wavelets ; Manifold-valued Data ; Sparse Regularization ; Symmetric Spaces; Proximal Point Algorithm; Extrinsic Sample Means; Center-of-mass; Subdivision Schemes; Riemannian-manifolds; Refinement Equations; Variational-problems; Bounded Variation; General Dilation; Corpus-callosum
ISSN (print) / ISBN
1540-3459
e-ISSN
1540-3467
Quellenangaben
Volume: 18,
Issue: 2,
Pages: 674-706
Publisher
Siam Publications
Publishing Place
Philadelphia
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)