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Radial basis functions and level set method for image segmentation using partial differential equation

机译:基于偏微分方程的径向基函数和水平集分割方法

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Combining nonlinear evolution equations, which arise from image segmentation using partial differential equation-based level set method, using radial basis functions, a meshless numerical algorithm is presented for image segmentation in this paper. Both globally supported and compactly supported radial basis functions are used to interpolate the level set function of the evolution equation with a high level of accuracy and smoothness. The nonlinear evolution equation is finally cast into ordinary differential equations and Euler's scheme is employed. Compared with traditional level set approaches, the presented algorithm is robust to initialization or even free of manual initialization, and avoids the complex and costly re-initialization of the level set function. The capability of the presented algorithm is demonstrated through some numerical experiments. (C) 2016 Elsevier Inc. All rights reserved.
机译:结合利用基于偏微分方程的水平集方法进行图像分割的非线性演化方程,利用径向基函数,提出了一种无网格数值算法进行图像分割。全局支持和紧密支持的径向基函数都用于以高水平的精度和平滑度插值演化方程的水平集函数。最后将非线性发展方程式转化为常微分方程式,并采用欧拉法。与传统的水平集方法相比,所提出的算法对初始化具有鲁棒性,甚至不需要手动初始化,并且避免了复杂且昂贵的水平集函数的重新初始化。通过一些数值实验证明了该算法的性能。 (C)2016 Elsevier Inc.保留所有权利。

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