通过对最小二乘支持向量机(Least squares support vector regression,LS-SVR)滤波特性的分析,给出了LS-SVR用于图像滤波的卷积模板构造方法,解决了LS-SVR在应用中需要求解的问题,在此基础上,提出了基于LS-SVR的开关型椒盐噪声滤波算法...通过对最小二乘支持向量机(Least squares support vector regression,LS-SVR)滤波特性的分析,给出了LS-SVR用于图像滤波的卷积模板构造方法,解决了LS-SVR在应用中需要求解的问题,在此基础上,提出了基于LS-SVR的开关型椒盐噪声滤波算法.滤波算法中以Maximum-minimum算子作为椒盐噪声检测器,利用滤波窗口内非噪声点构成LS-SVR的输入数据,使用事先构造出的LS-SVR滤波算子,对滤波窗口进行简单的卷积运算,实现了被椒盐噪声污染点数据的有效恢复,实验表明,本文提出的方法具有较好的细节保护能力和较强的噪声去除能力.展开更多
A new method of detecting abnormal sounding data based on LS-SVM is presented.The theorem proves that the trend surface filter is the especial result of LS-SVM.In order to depict the relationship of trend surface filt...A new method of detecting abnormal sounding data based on LS-SVM is presented.The theorem proves that the trend surface filter is the especial result of LS-SVM.In order to depict the relationship of trend surface filter and LS-SVM,a contrast is given.The example shows that abnormal sounding data could be detected effectively by LS-SVM when the training samples and kernel function are reasonable.展开更多
文摘通过对最小二乘支持向量机(Least squares support vector regression,LS-SVR)滤波特性的分析,给出了LS-SVR用于图像滤波的卷积模板构造方法,解决了LS-SVR在应用中需要求解的问题,在此基础上,提出了基于LS-SVR的开关型椒盐噪声滤波算法.滤波算法中以Maximum-minimum算子作为椒盐噪声检测器,利用滤波窗口内非噪声点构成LS-SVR的输入数据,使用事先构造出的LS-SVR滤波算子,对滤波窗口进行简单的卷积运算,实现了被椒盐噪声污染点数据的有效恢复,实验表明,本文提出的方法具有较好的细节保护能力和较强的噪声去除能力.
基金The National High-Tech Research and Development Program of China (863 Program) under contract No.2007AA12Z326the National Natural Science Foundation of China under contract Nos 40974010 and 40971306
文摘A new method of detecting abnormal sounding data based on LS-SVM is presented.The theorem proves that the trend surface filter is the especial result of LS-SVM.In order to depict the relationship of trend surface filter and LS-SVM,a contrast is given.The example shows that abnormal sounding data could be detected effectively by LS-SVM when the training samples and kernel function are reasonable.
