Total normal curvature regularization and its minimization for surface and image smoothing
Lu, Tianle and Chen, Ke and Duan, Yuping (2026) Total normal curvature regularization and its minimization for surface and image smoothing. SIAM Journal on Imaging Sciences, 19 (2). pp. 879-912. ISSN 1936-4954 (https://doi.org/10.1137/25m1782613)
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Abstract
We introduce a novel formulation for curvature regularization by penalizing normal curvatures from multiple directions. This total normal curvature regularization is capable of producing solutions with sharp edges and precise isotropic properties. To tackle the resulting high-order nonlinear optimization problem, we reformulate it as the task of finding the steady-state solution of a time-dependent partial differential equation (PDE) system. Time discretization is achieved through operator splitting, where each subproblem at the fractional steps either has a closed-form solution or can be efficiently solved using advanced algorithms. Our method circumvents the need for complex parameter tuning and demonstrates robustness to parameter choices. The efficiency and effectiveness of our approach have been rigorously validated in the context of surface and image smoothing problems.
ORCID iDs
Lu, Tianle, Chen, Ke
ORCID: https://orcid.org/0000-0002-6093-6623 and Duan, Yuping;
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Item type: Article ID code: 96219 Dates: DateEvent30 June 2026Published30 April 2026Published Online4 December 2025AcceptedSubjects: Science > Mathematics > Electronic computers. Computer science Department: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 11 May 2026 11:12 Last modified: 02 Jun 2026 07:13 URI: https://strathprints.strath.ac.uk/id/eprint/96219
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