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PDE-BASED MODELING OF IMAGE SEGMENTATION USING VOLUMIC FLOODING

机译:基于PDE的图像分割建模使用量洪水

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The classical case of morphological segmentation is based on the watershed transform, constructed by flooding the gradient image, which is seen as a topographic surface, with constant height speed. Changing the flooding criteria, (e.g constant-speed height, area or volume) yields different segmentation results. In the field of PDEs and curve evolution the classic watershed transform can be modelled as the solution of an eikonal PDE. In this paper we model the watershed segmentation based on a volume flooding criterion via a different eikonal PDE. Then we solve this PDE using the fast marching method, which is a specific algorithm from the methodology of level sets. In addition, we attempt to exploit the advantages of image segmentation using PDE-based volume flooding over the classic height flooding.
机译:形态分割的经典情况是基于流域变换,通过泛洪被视为地形表面的梯度图像构成,具有恒定的高速。改变洪水标准(例如恒速高度,区域或体积)产生不同的分段结果。在PDES和曲线上的领域中,经典的流域变换可以被建模为eikonal PDE的解决方案。在本文中,我们通过不同的eikonal pde基于体积泛滥标准来模拟流域分割。然后,我们使用快速行进方法解决此PDE,这是一种从级别的方法的特定算法。此外,我们试图利用在经典高度洪水上使用基于PDE的体积洪水来利用图像分割的优点。

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