基于偏微分方程扩散系数的图像去噪研究*

在偏微分方程P-M模型图像去噪过程中,扩散系数的选择会影响图像去噪的效果;为此提出了一个新的扩散系数模型来实现图像去噪.首先分析讨论了P-M模型中扩散系数和梯度阈值的选取对图像去噪的重要性;并对比了两个扩散系数的优点和缺点,在此基础上提出一个新的扩散系数;并应用到正则化P-M模型和四阶偏微分方程YK模型中进行数值离散实验.实验结果表明,采用新的扩散系数在正则化的P-M模型和YK模型的去噪效果教好,提出的扩散系数能够有效地进行图像去噪.

Image denoising of partial differential equations based on the diffusion coefficient

In the process of partial differential equations PM model image denoising, select the diffusion coefficient will affect the image denoising effect, had come out with a new model of the diffusion coefficient to achieve image denoising. First, discussed the importance of the diffusion coefficient of the PM model and the gradient threshold for image denoising, and compared the advantages and disadvantages of the two diffusion coefficients, and applied to the regularization PM model and fourth-order partial differential equations YK model discrete numerical experiments. Experimental results show that the new diffusion coefficient in the denoising effect is better in the regularization PM model and YK model, In this paper, the diffusion coefficient can be effectively denoising.