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);
}

test