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Multigrid Geometric Active Contour Models

机译:多网格几何主动轮廓模型

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Geometric active contour models are very popular partial differential equation-based tools in image analysis and computer vision. We present a new multigrid algorithm for the fast evolution of level-set-based geometric active contours and compare it with other established numerical schemes. We overcome the main bottleneck associated with most numerical implementations of geometric active contours, namely the need for very small time steps to avoid instability, by employing a very stable fully 2-D implicit-explicit time integration numerical scheme. The proposed scheme is more accurate and has improved rotational invariance properties compared with alternative split schemes, particularly when big time steps are utilized. We then apply properly designed multigrid methods to efficiently solve the occurring sparse linear system. The combined algorithm allows for the rapid evolution of the contour and convergence to its final configuration after very few iterations. Image segmentation experiments demonstrate the efficiency and accuracy of the method
机译:几何活动轮廓模型是图像分析和计算机视觉中非常流行的基于偏微分方程的工具。我们提出了一种新的多重网格算法,用于基于水平集的几何活动轮廓的快速演化,并将其与其他已建立的数值方案进行比较。通过采用非常稳定的全二维隐式-显式时间积分数值方案,我们克服了与几何活动轮廓的大多数数值实现相关的主要瓶颈,即需要非常小的时间步长以避免不稳定。与替代拆分方案相比,所提出的方案更加准确,并且具有改进的旋转不变性,尤其是在使用大时间步长的情况下。然后,我们应用适当设计的多网格方法来有效地解决出现的稀疏线性系统。组合算法可以使轮廓快速演化并在极少的迭代之后收敛到其最终配置。图像分割实验证明了该方法的有效性和准确性

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