改进的自适应加权中值滤波算法

Improved adaptive weighted median filtering algorithm

在分析了自适应算法和中心加权算法的原理和优势后,提出了一种改进的自适应加权中值滤波(IAWMF)算法。采用扩展边缘的方式,使原图像的所有像素点能够用噪声检测因子进行噪声检测,对含有噪声的图像采用自适应窗口(N×N)的中心加权算法进行滤波,可以有效降低邻域噪声点对滤波图像质量的影响。仿真结果表明:改进算法在高浓度椒盐噪声条件下获得的实验效果峰值信噪比(PSNR)、均值平方误差(MAE)、均值绝对误差(MSE)显著优于其他算法,在降噪和保持细节中取得很好的平衡。

An improved adaptive weighted median filtering（ IAWMF） algorithm is proposed,after analyzing the principle and advantages of the adaptive algorithm and the central weighted algorithm. Adopting the way of expanding edge,it can make all the pixels of the original image detected by noise detection factor and adopt center weighted filtering algorithm of adaptive window（ N × N） for filtering image containing noise,which can effectively reduce influence of the neighborhood noise point on quality of filtering image. Simulation results show that the experimental effect（ PSNR,MAE,MSE） acquired by proposed algorithm is better than other algorithms and achieve a good balance between noise reduction and preserving details.