改进的变分自适应中值滤波算法

Salt-and-pepper Noise Removal by Variational Method Based on Improved Adaptive Median Filter

为了更好地恢复被高密度椒盐噪声污染的图像,该文提出了一种基于两阶段方法去除图像椒盐噪声的算法。首先,利用改进的自适应中值滤波算法标识出图像中被污染的像素点,然后对被污染的像素点采用变分滤波的方法进行恢复。此方法利用了自适应中值滤波良好的噪点识别能力和变分滤波的细节保护的特性,对于噪声密度高达80%的图像依然可以达到很好的恢复效果。仿真结果验证了所提出算法的有效性,并且在效果上要明显优于传统的变分自适应中值滤波算法。

To improve the performance of salt-and-pepper noise removal,a two-stage scheme is proposed.In the first phase,an improved adaptive median filter is used to identify pixels which are likely to be contaminated by noise（noise candidates）.In the second phase,the image is restored using a variational method that applies only to those selected noise candidates.The proposed method can remove salt-and-pepper-noise with a noise level as high as 80%.Simulation results indicate that this algorithm is effective and better than traditional variational method based on adaptive median filter.