基于支持向量机的改进中值滤波算法

Improved Median Filtering Algorithm Based on Support Vector Machine

对椒盐噪声的特点以及标准中值滤波算法存在的不足,提出一种基于支持向量机的改进中值滤波算法.该算法首先对噪声图像进行中值滤波,并对滤波后图像去模糊化,然后用支持向量机分类确定去模糊化后图像中灰度值为最大值或最小值的像素点是否为噪声点,最后通过支持向量机回归预测将噪声点恢复为原始信号.仿真实验及仿真结果分析表明该算法可以有效地去除椒盐噪声,且有较高的峰值信噪比.

According to the characteristics of salt and pepper noise and the defects of the standard median filter algorithm, an improved median filtering algorithm based on support vector machine is proposed in this paper. At first, the algorithm filters the noise image by using median filtering and then defuzzification operations are performed on the filtered image. For those pixels in the defuzzified image whose gray scale values are the maximum or minimum value, support vector machine（SVM） classification is used to decide whether they are noise points. Finally support vector machine（SVM） regression is used to recover original signals from the noise points. Experiments and simulation analyses show that our algorithm can effectively remove salt and pepper noise, and has higher peak signal to noise ratio.