中文摘要：

针对现行的均值滤波算法存在的局限性,基于灰度修剪和均衡化的加权均值滤波算法对其进行改进.算法根据高斯噪声的特点及其对原图像的影响,对处于灰度概率峰值附近所对应的灰度进行修剪,再进行加权均值滤波.加权系数同时考虑灰度相关性与距离相关性,是灰度测度因子和距离测度因子的乘积.算法最后对加权均值滤波后图像进行分段的灰度均衡化.滤波实验的结果表明,相对于现行的均值滤波算法,本算法有着更好的滤波性能,在滤除噪声的同时,很好地保持图像的边缘和细节部分.

英文摘要：

Against the limitation of existing mean filtering algorithms,an improved weighted mean filtering algorithm is proposed by gray trimmed and equalization. According to Gaussian noise characteristics and its effect on original image,the corresponding gray is firstly trimmed to gray probability peak,and then the noise image is filtered by weighted mean. The weighted coefficient is the product of gray measure factor and distance measure factor,which takes gray correlation and distance correlation into consideration. Finally,the algorithm piecewise equalizes the image gray of weighted mean filtered. Experimental results demonstrate that the proposed algorithm has a significant better filtering performance in comparison with the existing mean filtering algorithms,which maintains image edges and details well in filtering noise.