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首页> 外文期刊>Inverse Problems: An International Journal of Inverse Problems, Inverse Methods and Computerised Inversion of Data >Discrete total variation of the normal vector field as shape prior with applications in geometric inverse problems
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Discrete total variation of the normal vector field as shape prior with applications in geometric inverse problems

机译:在几何逆问题中的应用,将普通矢量字段的离散总变化为形状

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摘要

An analogue of the total variation prior for the normal vector field along the boundary of piecewise flat shapes in 3D is introduced. A major class of examples are triangulated surfaces as they occur for instance in finite element computations. The analysis of the functional is based on a differential geometric setting in which the unit normal vector is viewed as an element of the two-dimensional sphere manifold. It is found to agree with the discrete total mean curvature known in discrete differential geometry. A split Bregman iteration is proposed for the solution of discretized shape optimization problems, in which the total variation of the normal appears as a regularizer. Unlike most other priors, such as surface area, the new functional allows for piecewise flat shapes. As two applications, a mesh denoising and a geometric inverse problem of inclusion detection type involving a partial differential equation are considered. Numerical experiments confirm that polyhedral shapes can be identified quite accurately.
机译:介绍了沿着3D分段平面边界的正常矢量场之前的总变化的模拟。主要类示例是三角形表面,因为它们发生在例如有限元计算中。该功能的分析基于差分几何设置,其中将单位正常向量被视为二维球形歧管的元件。发现它与离散微分几何形状已知的离散总平均曲率同意。提出了一种分割BREGMAN迭代,用于解决离散形状优化问题,其中正常的总变化显示为符号器。与大多数其他前沿(如表面积)不同,新功能允许分段平整形状。作为两个应用,考虑了涉及局部微分方程的网格去噪和包括夹杂物检测类型的几何逆问题。数值实验证实,可以非常准确地识别多面体形状。

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