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Edge-preserving based adaptive ICC method for image diffusion

机译:基于边缘保留的自适应ICC图像扩散方法

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Image diffusion is the underlying machine vision research method, and is frequently used to remove image noise. In this paper, we propose a new kernel function for image diffusion by combining the intervening contour (IC) and the color (C) component, called ICC kernel function, which can smooth inner messy texture while maintaining image structure. The intervening contour is used to ensure the diffusion process not to cross the boundary, and the color component ensures the photometric similarity between two pixels. A pixel-segmentation-property based approach is applied to adaptively select the kernel parameters. Experiments show that the adaptive ICC method has better performance of edge-preserving and messy texture smoothing than bilateral filtering and mean shift. Our adaptive ICC method enhances image features representation and helps to improve high-level recognition algorithms.
机译:图像扩散是基础的机器视觉研究方法,经常用于消除图像噪声。在本文中,我们通过结合中间轮廓(IC)和颜色(C)分量,提出了一种用于图像扩散的新内核函数,称为ICC内核函数,它可以在保持图像结构的同时平滑内部杂乱的纹理。中间轮廓用于确保扩散过程不会越过边界,颜色分量可确保两个像素之间的光度相似度。基于像素分割属性的方法被应用于自适应地选择内核参数。实验表明,自适应ICC方法比双边滤波和均值漂移具有更好的边缘保留和杂乱纹理平滑性能。我们的自适应ICC方法可增强图像特征表示,并有助于改进高级识别算法。

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