中文摘要：

本文利用原始图像和图像均值之间的相关性提出了一种新的自适应加权图像去噪算法。第一步是区分灰度系数的关联矩阵和VH阈值，而灰度系数的关联矩阵是用来计算原始图像和图像均值的。第二步是根据噪声图像和图像均值的相关性系数计算噪声点的值来实现自适应加权图像去噪。最后，我们选择信噪比，峰值信噪比和平均误差测试不同的噪声水平下的去噪效果。结果表明，此方法可减少图像模糊，保持边缘和细节信息的完整性，并具有良好的去噪效果。

英文摘要：

In this paper, a new adaptive weighted image denoising algorithm which is about the correlation between the original image and the mean image has been proposed. The first step is to distinguish the gray correlation matrix of the coefficients and VH threshold, however, the the gray coefficient associated matrix is used to calculate the mean of the original image and the mean image. The second step calculates the correlation coefficient according to the noise image and the mean image to achieve the adaptive weighted image denoising. Finally, we choose the signal-to-noise ratio, the peak signal-to-noise ratio and the average error to test different noise levels. The results show that this method can reduce image blur, maintain the integrity of edge and detail information, and has a good denoising effect.