针对标准中值滤波方法存在的不足，结合均值思想提出两种改进的中值滤波算法，即加权快速中值滤波算法和加权自适应中值滤波算法，MATLAB实验证实两种方法均能更好地保存原始图像的细节和边缘。比较两种新方法得出以下结论：加权改进中值滤波算法对低密度的脉冲噪声去噪效果明显，对于高密度脉冲噪声去噪效果不理想，但能大大提高中值滤波的运行速度，对数字图像实时处理意义很大；加权自适应中值滤波算法能够有效地消除被污染图像中的高密度脉冲噪声，较标准中值滤波具有更优良的滤波性能，较加权快速中值滤波算法在去噪方面有更好的鲁棒性。

Based on the shortcomings of standard median filtering, this paper puts forward two improved median filtering algorithms referred as the weighted fast median filtering algorithm and the weighted adaptive median filtering algorithm. The experiment results with MATLAB show that both of them can retain the original image details and edge nicely. The two improved algorithms are compared and the comparison indicates that the weighted fast median filtering algorithm has a significant effect on low-density impulse noise, while having non-ideal effect on high-density impulse noise, it could improve the speed of median filtering operation and could be used for digital images real-time processing; the weighted adaptive median filtering algorithm could effectively eliminate the high-density impulse noise from polluted images, and it has more superior filtering performance than the standard median filtering while having better robustness on de-noising than the weighted fast median filtering algorithm.