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Color Image Segmentation Based on Vectorial Multiscale Diffusion with Inter-scale Linking

机译:基于矢量多尺度扩散和尺度间链接的彩色图像分割

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摘要

We propose a segmentation scheme for digital color images using vectorial multiscale anisotropic diffusion. By integrating the edge information, diffusion based schemes can remove noise effectively and create fine to coarse set of images known as scale-space. Segmentation is performed by effectively tracking edges in an inter-scale manner across this scale space family of images. The regions are connected according to color coherency, and scale relation along time axis of the family is taken into account for the final segmentation result. Fast total variation diffusion and anisotropic diffusion facilitate denoising and create homogenous regions separated by strong edges. They provide a roadmap for further segmentation with persistent edges and flat regions. The scheme is general in the sense that other anisotropic diffusion schemes can be incorporated depending upon the requirement. Numerical simulations show the advantage of the proposed scheme on noisy color images.
机译:我们提出了使用矢量多尺度各向异性扩散的数字彩色图像分割方案。通过整合边缘信息,基于扩散的方案可以有效地去除噪声并创建精细到粗糙的图像集,称为比例空间。通过以跨尺度的方式跨此尺度空间图像族有效跟踪边缘来执行分割。区域根据颜色连贯性进行连接,并考虑沿族时间轴的比例关系以获取最终的分割结果。快速的总变化扩散和各向异性扩散有助于降噪并创建由强边缘分隔的均匀区域。它们为使用持久边缘和平坦区域进行进一步细分提供了路线图。该方案是一般的,在某种意义上,可以根据需要并入其他各向异性扩散方案。数值模拟表明了该方案在噪声彩色图像上的优势。

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