图像处理-基于OpenCV实现的图像滤波算法之BilateralFilter.zip

#include <opencv2/core.hpp> #include <opencv2/highgui.hpp> #include <opencv2/imgproc.hpp> #include <iostream> //////////////////////////// //获取高斯模板（空间模板） /////////////////////////// void getGausssianMask(cv::Mat& Mask, cv::Size wsize, double spaceSigma){ Mask.create(wsize, CV_64F); int h = wsize.height; int w = wsize.width; int center_h = (h - 1) / 2; int center_w = (w - 1) / 2; double sum = 0.0; double x, y; for (int i = 0; i < h; ++i){ y = pow(i - center_h, 2); double* Maskdate = Mask.ptr<double>(i); for (int j = 0; j < w; ++j){ x = pow(j - center_w, 2); double g = exp(-(x + y) / (2 * spaceSigma * spaceSigma)); Maskdate[j] = g; sum += g; } } } //////////////////////////// //获取色彩模板（值域模板） /////////////////////////// void getColorMask(std::vector<double> &colorMask , double colorSigma){ for (int i = 0; i < 256; ++i){ double colordiff = exp(-(i*i) / (2 * colorSigma * colorSigma)); colorMask.push_back(colordiff); } } //////////////////////////// //双边滤波 /////////////////////////// void bilateralfiter(cv::Mat& src, cv::Mat& dst, cv::Size wsize, double spaceSigma, double colorSigma){ cv::Mat spaceMask; std::vector<double> colorMask; cv::Mat Mask0 = cv::Mat::zeros(wsize, CV_64F); cv::Mat Mask1 = cv::Mat::zeros(wsize, CV_64F); cv::Mat Mask2 = cv::Mat::zeros(wsize, CV_64F); getGausssianMask(spaceMask, wsize, spaceSigma);//空间模板 getColorMask(colorMask, colorSigma);//值域模板 int hh = (wsize.height - 1) / 2; int ww = (wsize.width - 1) / 2; dst.create(src.size(), src.type()); //边界填充 cv::Mat Newsrc; cv::copyMakeBorder(src, Newsrc, hh, hh, ww, ww, cv::BORDER_REPLICATE);//边界复制; for (int i = hh; i < src.rows + hh; ++i){ for (int j = ww; j < src.cols + ww; ++j){ double sum[3] = { 0 }; int graydiff[3] = { 0 }; double space_color_sum[3] = { 0.0 }; for (int r = -hh; r <= hh; ++r){ for (int c = -ww; c <= ww; ++c){ if (src.channels() == 1){ int centerPix = Newsrc.at<uchar>(i, j); int pix = Newsrc.at<uchar>(i + r, j + c); graydiff[0] = abs(pix - centerPix); double colorWeight = colorMask[graydiff[0]]; Mask0.at<double>(r + hh, c + ww) = colorWeight * spaceMask.at<double>(r + hh, c + ww);//滤波模板 space_color_sum[0] = space_color_sum[0] + Mask0.at<double>(r + hh, c + ww); } else if (src.channels() == 3){ cv::Vec3b centerPix = Newsrc.at<cv::Vec3b>(i, j); cv::Vec3b bgr = Newsrc.at<cv::Vec3b>(i + r, j + c); graydiff[0] = abs(bgr[0] - centerPix[0]); graydiff[1] = abs(bgr[1] - centerPix[1]); graydiff[2] = abs(bgr[2] - centerPix[2]); double colorWeight0 = colorMask[graydiff[0]]; double colorWeight1 = colorMask[graydiff[1]]; double colorWeight2 = colorMask[graydiff[2]]; Mask0.at<double>(r + hh, c + ww) = colorWeight0 * spaceMask.at<double>(r + hh, c + ww);//滤波模板 Mask1.at<double>(r + hh, c + ww) = colorWeight1 * spaceMask.at<double>(r + hh, c + ww); Mask2.at<double>(r + hh, c + ww) = colorWeight2 * spaceMask.at<double>(r + hh, c + ww); space_color_sum[0] = space_color_sum[0] + Mask0.at<double>(r + hh, c + ww); space_color_sum[1] = space_color_sum[1] + Mask1.at<double>(r + hh, c + ww); space_color_sum[2] = space_color_sum[2] + Mask2.at<double>(r + hh, c + ww); } } } //滤波模板归一化 if(src.channels() == 1) Mask0 = Mask0 / space_color_sum[0]; else{ Mask0 = Mask0 / space_color_sum[0]; Mask1 = Mask1 / space_color_sum[1]; Mask2 = Mask2 / space_color_sum[2]; } for (int r = -hh; r <= hh; ++r){ for (int c = -ww; c <= ww; ++c){ if (src.channels() == 1){ sum[0] = sum[0] + Newsrc.at<uchar>(i + r, j + c) * Mask0.at<double>(r + hh, c + ww); //滤波 } else if(src.channels() == 3){ cv::Vec3b bgr = Newsrc.at<cv::Vec3b>(i + r, j + c); //滤波 sum[0] = sum[0] + bgr[0] * Mask0.at<double>(r + hh, c + ww);//B sum[1] = sum[1] + bgr[1] * Mask1.at<double>(r + hh, c + ww);//G sum[2] = sum[2] + bgr[2] * Mask2.at<double>(r + hh, c + ww);//R } } } for (int k = 0; k < src.channels(); ++k){ if (sum[k] < 0) sum[k] = 0; else if (sum[k]>255) sum[k] = 255; } if (src.channels() == 1) { dst.at<uchar>(i - hh, j - ww) = static_cast<uchar>(sum[0]); } else if (src.channels() == 3) { cv::Vec3b bgr = { static_cast<uchar>(sum[0]), static_cast<uchar>(sum[1]), static_cast<uchar>(sum[2]) }; dst.at<cv::Vec3b>(i - hh, j - ww) = bgr; } } } } int main(){ cv::Mat src = cv::imread("I:\\Learning-and-Practice\\2019Change\\Image process algorithm\\Img\\woman1.jpeg"); if (src.empty()){ return -1; } cv::Mat dst; double spaceSigma = 10; double colorSigma = 30; bilateralfiter( src, dst, cv::Size(23,23), spaceSigma, colorSigma); cv::namedWindow("src", CV_WINDOW_NORMAL); cv::imshow("src", src); cv::namedWindow("双边滤波",CV_WINDOW_NORMAL); cv::imshow("双边滤波", dst); cv::imwrite("I:\\Learning-and-Practice\\2019Change\\Image process algorithm\\Image Filtering\\BilateralFilter\\woman1.jpg", dst); cv::waitKey(0); return 0; }