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

机译:Schrodinger波形方程方法eikonal公式:图像分析应用

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As Planck's constant h (treated as a free parameter) tends to zero, the solution to the eikonal equation |{nabla}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:作为普朗克常数h(作为自由参数处理的)趋于零,该溶液到程函方程| {nabla} S(X)| = F(X)可以被日益密切通过溶液到相应的薛定谔方程近似。当强制函数f(X)被设置为一个,我们得到了欧几里得距离函数问题。我们表明,相应的薛定谔方程具有可以被表示为离散的卷积,并有效地计算使用快速傅里叶变换(FFT)的封闭形式的解。程函方程在图像分析,即多个应用程序。对形状的轮廓,从点云和图像分割为几个表面重建符号距离函数。我们表明,距离函数的符号,它的梯度和曲率都可以写在封闭的形式,表现为离散的卷积,并使用FFT的有效计算。这里注意到的是,在2D距离函数的符号表示为卷数计算。对于一般程函问题,我们提出了一个扰动系列的办法,结果在离散的卷积的序列再次有效地利用FFT的计算。我们比较我们用快速扫描方法获得这些方法的结果,封闭形式的解决方案(如果可用)和Dijkstra的最短路径算法。

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