Anisotropic diffusion based on directional consistency

Zhiming Wang, Hong Bao, Li Zhang
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引用次数: 2

Abstract

A novel image anisotropic diffusion algorithm is proposed. As noise was more likely to be random, directional gray level consistency gives a feasible discrimination between noise and image structure. Firstly, a measurement of directional consistency was defined. Then, this consistency was transformed into diffusion weight, and diffusivity of different directions was computed from gradient and diffusion weight. At last, anisotropic diffusion was realized based on this directional different diffusivity. Some typical image diffusion algorithms were compared with proposed algorithm. Experimental results on both synthetic and real image with hybrid noise show the efficiency of proposed algorithm.
基于方向一致性的各向异性扩散
提出了一种新的图像各向异性扩散算法。由于噪声更可能是随机的,方向灰度一致性为噪声和图像结构之间的区分提供了可行的方法。首先,定义了方向一致性的度量。然后将该一致性转化为扩散权值,由梯度和扩散权值计算不同方向的扩散率。最后,在此基础上实现了各向异性扩散。对几种典型的图像扩散算法进行了比较。在混合噪声的合成图像和真实图像上的实验结果表明了该算法的有效性。
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