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Partial differential equations in image analysis: Applications, implementations, and extensions (Mathematical morphology).

机译:图像分析中的偏微分方程:应用,实现和扩展(数学形态学)。

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Partial Differential Equations (PDE's) have played important roles in image processing and image analysis for years. Using PDE's, one can model the images in a continuous domain, see existing methods in a different viewpoint, and combine multiple algorithms together. Furthermore, high accuracy and stability can be naturally obtained.; In this thesis, we propose some interesting applications, implementations and extensions of the PDE's in image analysis.; First, we extend the concept of level-lines to vector-valued images. Consistent with the scalar case, we define the level-lines of vector-valued images as the integral curves of the directions of minimal vectorial change. These directions and the magnitude of change are computed using classical Riemannian geometry. To exemplify the use of this new concept, we propose a novel approach to scalar representation of vector images using PDE's.; Second, we show the connections between vector median filters, morphological operators and geometric PDE's. We'll show how the concept of Median filter is related to morphological inf-sup operators and then extend this concept to vector-valued images. Considering a lexicographic order to define orders between vectors in R N, we also provide new definitions of the discrete and continuous versions of Vector Median Filters by means of a coupled system of geometric PDE's.; Third, we gives an example of the use of PDE-based segmentation techniques to detect the boundaries of skin lesions, which helps the dermatologist diagnose Malignant Melanoma, or skin cancers. A novel, morphological approach to remove the hairs covering the object of interest is also presented.; Fourth, we propose a very simple algorithm to skeletonize given gray-scale images using modified erosion/dilation equations without the need of pre-segmentation or addition of shock capturing schemes. With this scheme, the skeleton of multiple objects can be simultaneously computed.; Finally, we introduce our software, ImageRepair, which is an integration of many PDE-based image processing routines. This MS-Windows based user-friendly system is designed to assist with the analysis of images. This is a first of this kind of software that is made available to the research community. The fundamentals of some selected features of this software package are described with a few screen-shots.
机译:多年以来,偏微分方程(PDE)在图像处理和图像分析中发挥了重要作用。使用PDE,可以在连续域中对图像进行建模,以不同的视角查看现有方法,并将多种算法结合在一起。此外,可以自然地获得高精度和稳定性。本文提出了PDE在图像分析中的一些有趣的应用,实现和扩展。首先,我们将水平线的概念扩展到矢量值图像。与标量情况一致,我们将矢量值图像的水平线定义为最小矢量变化方向的积分曲线。使用经典的黎曼几何来计算这些方向和变化幅度。为了举例说明这个新概念的使用,我们提出了一种使用PDE对矢量图像进行标量表示的新颖方法。其次,我们展示了矢量中值滤波器,形态算子和几何PDE之间的联系。我们将说明中值滤波器的概念与形态学infsup运算符如何相关,然后将该概念扩展到矢量值图像。考虑到按字典顺序定义R N中向量之间的顺序,我们还通过几何PDE的耦合系统提供了向量中值滤波器离散和连续版本的新定义。第三,我们举一个使用基于PDE的分割技术来检测皮肤病变边界的示例,这有助于皮肤科医生诊断恶性黑色素瘤或皮肤癌。还提出了一种新颖的形态学方法来去除覆盖目标物体的毛发。第四,我们提出了一种非常简单的算法,可以使用修改后的腐蚀/膨胀方程式对给定的灰度图像进行骨架化,而无需预先分割或添加冲击捕获方案。使用这种方案,可以同时计算多个对象的骨架。最后,我们介绍我们的软件ImageRepair,它是许多基于PDE的图像处理例程的集成。这个基于MS-Windows的用户友好系统旨在帮助分析图像。这是向研究团体提供的此类软件中的第一个。通过一些屏幕快照描述了该软件包某些选定功能的基础。

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