Discrete total variation of the normal vector field as shape prior with applications in geometric inverse problems
DOI10.1088/1361-6420/ab6d5cOpenAlexW3099016725MaRDI QIDQ5000592
Stephan Schmidt, José Vidal-Nuñez, Ronny Bergmann, Marc Herrmann, Roland Griesse
Publication date: 14 July 2021
Published in: Inverse Problems (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1908.07916
shape optimizationdiscrete differential geometrygeometric inverse problemsplit Bregman iterationinclusion detectiontotal variation of the normal
Numerical methods for partial differential equations, boundary value problems (65Nxx) Numerical methods in optimal control (49Mxx) Communication, information (94Axx) Computing methodologies and applications (68Uxx) Numerical methods for mathematical programming, optimization and variational techniques (65Kxx)
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- Nonlinear total variation based noise removal algorithms
- Restoration of manifold-valued images by half-quadratic minimization
- Bilevel parameter learning for higher-order total variation regularisation models
- Automated solution of differential equations by the finite element method. The FEniCS book
- Maps of bounded variation with values into a manifold: total variation and relaxed energy
- Electrical impedance tomography using level set representation and total variational regularization
- A discrete Laplace-Beltrami operator for simplicial surfaces
- Computing Medians and Means in Hadamard Spaces
- A Backprojection Algorithm for Electrical Impedance Imaging
- The Split Bregman Method for L1-Regularized Problems
- A Parallel Douglas–Rachford Algorithm for Minimizing ROF-like Functionals on Images with Values in Symmetric Hadamard Manifolds
- Curvatures of Smooth and Discrete Surfaces
- Iterative total variation schemes for nonlinear inverse problems
- A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
- Electrical Impedance Tomography
- A Graph Framework for Manifold-Valued Data
- Computational Methods for Inverse Problems
- Automated parameter selection in the ${L}^{1} \mbox{-} {L}^{2}$-TV model for removing Gaussian plus impulse noise
- On the reinitialization procedure in a narrow-band locally refined level set method for interfacial flows
- Unified form language