局部均方差滤波(磨皮)

note

锚点灰度值用原图像对应点的原灰度值和局部均值加权得到

局部均值由掩膜区域计算得到

权重由局部方差与用户输入参数计算确定

code

// 局部均方差滤波
/*\brief 局部均方差滤波\param src:原矩阵，单通道\param res:结果矩阵\param size:掩膜矩形大小，长宽都是奇数\param parameter:均值，方差权重因子
*/
void MyPartMeanVarianceFilter(Mat& src, Mat& res, Size& size, double parameter) {if ((src.channels() > 1) || (res.channels() > 1)) {return;}if ((size.width / 2 == 0) || (size.height / 2 == 0)) {return;}if (parameter < 0) {return;}int srcType = src.type();src.copyTo(res);src.convertTo(src, CV_64FC1);res.convertTo(res, CV_64FC1);int anchor_c = size.width / 2;int anchor_r = size.height / 2;for (int r = 0; r+size.height <= src.rows; r=r+1) {for (int c = 0; c+size.width <= src.cols; c=c+1) {Rect roi;roi.x = c;roi.y = r;roi.width = size.width;roi.height = size.height;Mat tmp = src(roi);Mat mean;	// 均值Mat sigma;	// 标准差meanStdDev(tmp, mean, sigma);double fMean = mean.at<double>(0);double fSigma = sigma.at<double>(0);double fSigma2 = fSigma * fSigma;	// 方差double k = fSigma2 / (fSigma2 + parameter);double origin = src.at<double>(r+anchor_r,c+anchor_c);double out = (1 - k) * fMean + k * origin;	// 锚点灰度值由原灰度值和局部均值加权得到res.at<double>(r+anchor_r,c+anchor_c) = out;// printf("origin:%lf, fMean:%lf, out:%lf\n", origin, fMean, out);}}src.convertTo(src, srcType);res.convertTo(res, srcType);
}