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A Schroedinger Wave Equation Approach to the Eikonal Equation: Application to Image Analysis

机译:Schroedinger波动方程方法的Eikonal方程:在图像分析中的应用

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摘要

As Planck's constant h (treated as a free parameter) tends to zero, the solution to the eikonal equation |▽S(X)| = f(X) can be increasingly closely approximated by the solution to the corresponding Schrodinger equation. When the forcing function f(X) is set to one, we get the Euclidean distance function problem. We show that the corresponding Schrodinger equation has a closed form solution which can be expressed as a discrete convolution and efficiently computed using a Fast Fourier Transform (FFT). The eikonal equation has several applications in image analysis, viz. signed distance functions for shape silhouettes, surface reconstruction from point clouds and image segmentation being a few. We show that the sign of the distance function, its gradients and curvature can all be written in closed form, expressed as discrete convolutions and efficiently computed using FFTs. Of note here is that the sign of the distance function in 2D is expressed as a winding number computation. For the general eikonal problem, we present a perturbation series approach which results in a sequence of discrete convolutions once again efficiently computed using FFTs. We compare the results of our approach with those obtained using the fast sweeping method, closed-form solutions (when available) and Dijkstra's shortest path algorithm.
机译:由于普朗克常数h(作为自由参数)趋于零,因此对本征方程|▽S(X)|的解= f(X)可以通过相应的薛定inger方程的解越来越接近。当强制函数f(X)设置为1时,我们得到了欧式距离函数问题。我们表明,相应的薛定equation方程具有闭式解,可以将其表示为离散卷积,并使用快速傅立叶变换(FFT)进行有效计算。 eikonal方程在图像分析中有多种应用,即。带符号的距离函数可用于形状轮廓,从点云进行表面重构以及图像分割。我们表明,距离函数的符号,其梯度和曲率都可以以封闭形式编写,表示为离散卷积并使用FFT进行有效计算。这里值得注意的是,二维函数中距离函数的符号表示为绕组数计算。对于一般的自然问题,我们提出了一种扰动级数方法,该方法会导致一系列离散卷积,再一次使用FFT进行有效计算。我们将我们的方法的结果与使用快速扫描方法,闭式解(如果有)和Dijkstra最短路径算法获得的结果进行比较。

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