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A time-dependent anisotropic diffusion image smoothing method

机译:时变各向异性扩散图像平滑方法

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In this paper, a time-dependent anisotropic diffusion image smoothing method is proposed with attempting to address the limitations in the traditional algorithms. To this end, we suggest a new diffusion coefficient and set the parameters that are the Gaussian scale and the gradient threshold gradually decreasing with time, which is significant to preserve edge and boundary features. The stopping time is dependent on an iterative SNR measure, so as to avoid the excessive smoothing problem. An efficient numerical schema is used for the method implementation. Experimental results represent that the time-dependent anisotropic diffusion image smoothing method is capable of reducing noise efficiently and preserving shaper boundaries.
机译:为了解决传统算法的局限性,提出了一种基于时间的各向异性扩散图像平滑方法。为此,我们提出了一个新的扩散系数,并设置了高斯尺度和梯度阈值随时间逐渐减小的参数,这对于保留边缘和边界特征非常重要。停止时间取决于迭代的SNR度量,以避免过度的平滑问题。有效的数字方案用于该方法的实现。实验结果表明,基于时间的各向异性扩散图像平滑方法能够有效降低噪声并保持整形边界。

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