一种改进的自适应中值滤波算法

An Improved Adaptive Median Filtering Algorithm

针对椒盐噪声的特点,提出了一种改进的自适应中值滤波算法。该算法通过对小窗口内非噪声点的检测来决定是增大滤波窗口还是选择输出。新算法尽可能地减小了滤波窗口,使得图像细节得到更好的保持。数值试验结果表明,新算法能够在有效抑制噪声的同时更好地保持图像细节信息,尤其在高概率密度噪声条件(>70%)下也能取得较好的结果,比传统自适应中值滤波算法的PSNR提高了3 dB以上,算法执行效率提高了近5倍,是一种简单、快速且有效的椒盐噪声滤除算法,在实际应用中有利于实现实时处理。

According to the characteristics of Salt-and-Pepper noise, an improved adaptive filtering （]AMF） algorithm is proposed in this paper. The non-noise pixels are deteted in a small window to decide to put out the pixel value or enlarge the filtering window size according to the non-noise pixels. The filtering window size is reduced as small as possibl. The better results of detail preserving are obtained. Numerical results show that the new algorithm removes noise effectively and gets better results of detail preserving at the same time. Especially in high noise probability density （2〉70%）, compared with AM_F, the PSNR of new algorithm is improved more than 3 dB and the efficiency is increased nearly five times. It can be applied to real-time processing.