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Super-Resolution Surface Reconstruction From Few Low-Resolution Slices
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Super-Resolution Surface Reconstruction From Few Low-Resolution Slices

Yiyao Zhang, Ke Chen 和 Shang-Hua Yang
Inverse Problems and Imaging, 卷.18(2), 頁碼.447-479
04/2024
Web of Science ID: WOS:001073442500001

摘要

alternating direction method of multipliers discrete geometry Euler-Elastica energy gaussian curvature mean curvature perimeter energy phase-field approximation Surface reconstruction variational model willmore energy Γ-convergence Analysis Modeling and Simulation Discrete Mathematics and Combinatorics Control and Optimization
In many imaging applications where segmented features (e.g. blood vessels) are further used for other numerical simulations (e.g. finite element analysis), the obtained surfaces do not have fine resolutions suitable for the task. Increasing the resolution of such surfaces becomes crucial. This paper proposes a new variational model for solving this problem, based on an Euler-Elastica-based regulariser. Further, we propose and implement two numerical algorithms for solving the model, a projected gradient descent method and the alternating direction method of multipliers. Numerical experiments using real-life examples (including two from outputs of another variational model) have been illustrated for effectiveness. The advantages of the new model are shown through quantitative comparisons by the standard deviation of Gaussian curvatures and mean curvatures from the viewpoint of discrete geometry.

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https://doi.org/10.3934/ipi.2023040檢視
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引用書目主題
5 Physics
5.214 Statistical Mechanics
5.214.1798 Cahn-Hilliard Equation
Web Of Science研究領域
Mathematics, Applied
Physics, Mathematical
ESI研究領域
Mathematics

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