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首页> 外文期刊>Quarterly of Applied Mathematics >LEFT-INVARIANT PARABOLIC EVOLUTIONS ON SE(2)AND CONTOUR ENHANCEMENT VIA INVERTIBLE ORIENTATION SCORES PART II: NONLINEAR LEFT-INVARIANT DIFFUSIONS ON INVERTIBLE ORIENTATION SCORES
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LEFT-INVARIANT PARABOLIC EVOLUTIONS ON SE(2)AND CONTOUR ENHANCEMENT VIA INVERTIBLE ORIENTATION SCORES PART II: NONLINEAR LEFT-INVARIANT DIFFUSIONS ON INVERTIBLE ORIENTATION SCORES

机译:SE(2)上的左不变抛物线演化和通过可旋转取向分数进行的轮廓增强第二部分:可旋转取向分数的非线性左不变分布

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摘要

By means of a special type of wavelet unitary transform we construct an orientation score from a grey-value image. This orientation score is a complex-valued function on the 2D Euclidean motion group SE(2) and gives us explicit information on the presence of local orientations in an image. As the transform between image and orientation score is unitary we can relate operators on images to operators on orienta-tion scores in a robust manner. Here we consider nonlinear adaptive diffusion equations on these invertible orientation scores. These nonlinear diffusion equations lead to clear improvements of the celebrated standard "coherence enhancing diffusion" equations on images as they can enhance images with crossing contours. Here we employ differen-tial geometry on SE(2) to align the diffusion with optimized local coordinate systems attached to an orientation score, allowing us to include local features such as adaptive curvature in our diffusions.
机译:通过特殊类型的小波unit变换,我们从灰度值图像构造方向分数。该方向分数是2D欧式运动组SE(2)上的复数值函数,可为我们提供有关图像中局部方向存在的明确信息。由于图像和方向得分之间的转换是统一的,因此我们可以以健壮的方式将图像上的算子与方向得分上的算子联系起来。在这里,我们考虑基于这些可逆取向分数的非线性自适应扩散方程。这些非线性扩散方程可以显着改善图像上著名的标准“相干增强扩散”方程,因为它们可以增强具有交叉轮廓的图像。在这里,我们在SE(2)上采用微分几何来使扩散与附加到方向分数的优化局部坐标系对齐,从而使我们能够在扩散中包括局部特征,例如自适应曲率。

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