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Image Denoising Method Based on Weighted Total Variational Model with Edge Operator

机译:基于加权总变分模型与边缘操作员的图像去噪方法

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In order to eliminate image noise effectively, the weighted total variation algorithm based on edge detection is proposed. By calculating the amplitude of the edge operator of the image, accurate estimates of edge weights are achieved, and then the weight of the canny operator is used to weigh the Lagrangian multiplier, which is no longer a global variable, so that the filter has a better edge protection feature. Theoretical analysis and experimental results show that the method can remove noise while preserving the edge details of the image more completely. The step effects of the total variation model is effectively suppressed, and has a better performance in terms of structural similarity and the visual effect of image.
机译:为了有效地消除图像噪声,提出了基于边缘检测的加权总变化算法。通过计算图像的边缘操作员的幅度,实现了边缘权重的精确估计,然后使用罐头运算符的重量来称量拉格朗日乘法器,这不再是全局变量,因此过滤器具有更好的边缘保护功能。理论分析和实验结果表明,该方法可以更完全地保留图像的边缘细节的同时消除噪声。总变化模型的阶跃效果被有效地抑制,并且在结构相似性和图像的视觉效果方面具有更好的性能。

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