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An High Order Finite Co-volume Scheme for Denoising Using Radial Basis Functions

机译:使用径向基函数进行降噪的高阶有限体积算法

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In this work we investigate finite co-volume methods for solving Partial Differential Equation (PDE) based diffusion models for noise removal in functional surfaces. We generalized the model proposed by Tai et al. [1][2] based on the reconstruction of a noise-reduced surface from the smoothed normal field, considering a curvature preserving term. The discretization of the PDE model by basic finite co-volume schemes on unstructured grids is investigated. The accuracy of the numerical model is then improved by using an higher order optimal recovery based on Radial Basis Functions (RBF). Preliminary numerical results demonstrate the effectiveness of the new numerical approach.
机译:在这项工作中,我们研究了有限的共体积方法,用于求解基于偏微分方程(PDE)的扩散模型,以消除功能表面中的噪声。我们推广了Tai等人提出的模型。 [1] [2]基于从平滑法线场重构的降噪表面,并考虑了曲率保持项。研究了在非结构网格上通过基本有限协体积方案对PDE模型的离散化。然后,通过使用基于径向基函数(RBF)的更高阶最优恢复来提高数值模型的准确性。初步的数值结果证明了新数值方法的有效性。

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