标签:continue 大小 ace ble size waitkey 复制 ++ sigma
#include <opencv2\highgui\highgui.hpp> #include <iostream> #include<vector> using namespace cv; using namespace std; void GetGaussianKernel(double*& gaus_1, const int size, const double sigma_s); void gaussianFilter2(const vector<uchar>& corrupted, vector<uchar> &smooth, double*& templates,const int width,const int height, const double sigma_r, const int size_m); int main() { const double sigma_r = 30; //值域的sigma const double PI = 4.0*atan(1.0); //圆周率π赋值 const int size_m = 5; //模板大小 const double sigma_s = 10; //空间域的sigma double *templates; templates = new double[size_m*size_m]; GetGaussianKernel(templates, size_m, sigma_s); Mat img = imread("123.jpg", 3); // namedWindow("MyWindow"); // imshow("MyWindow", img); vector<uchar> array(img.rows*img.cols*3); if (img.isContinuous()) { array.assign(img.datastart, img.dataend); } vector<uchar> no(img.rows*img.cols*3); gaussianFilter2(array, no, templates ,int(img.cols)*3, img.rows,sigma_r,size_m); Mat now((int)img.rows, (int)img.cols, CV_8UC3 ); for (int i = 0; i < img.rows; i++) for (int j = 0; j < img.cols; j++) { now.at<Vec3b>(i, j)[0] = no[i*img.cols*3 + j*3]; now.at<Vec3b>(i, j)[1] = no[i*img.cols*3 + j*3 + 1]; now.at<Vec3b>(i, j)[2] =no[i*img.cols*3 + j*3 + 2]; } imwrite("1123.jpg", now); namedWindow("MyWindow1"); imshow("MyWindow1", now); waitKey(0); return 0; } void GetGaussianKernel(double*& gaus_1, const int size, const double sigma_s) { double **gaus = new double*[size]; for (int i = 0; i<size; i++)gaus[i] = new double[size]; double sum = 0; for (int i = -size / 2; i<size / 2 + 1; i++) { for (int j = -size / 2; j<size / 2 + 1; j++) { gaus[i + size / 2][j + size / 2] = exp(-((i*i) + (j*j)) / (2 * sigma_s*sigma_s)); sum += gaus[i + size / 2][j + size / 2]; } } for (int i = 0; i<size; i++) { for (int j = 0; j<size; j++) { gaus[i][j] /= sum; gaus_1[i*size + j] = gaus[i][j]; //使用一维更简单 } } return; } void gaussianFilter2(const vector<uchar>& corrupted, vector<uchar> &smooth,double*& templates,const int width,const int height,const double sigma_r, const int size_m) { int len = size_m / 2; smooth = corrupted; //复制像素 for (int j = 0; j<height ; j++) { //边缘不处理 for (int i = 0; i<width ; i++) { double sum = 0; int index = 0; double sum_c = 0; double temp = 0; for (int m = j - len; m<j + len + 1; m++) { for (int n = i - 3 * len; n<i + 3 * len + 1; n += 3) { if (m<0 || n<0 || m>height - 1 || n>width - 1)continue; //边缘处理 temp = templates[index++] * exp(-(corrupted[m*width + n] - corrupted[j*width + i])*(corrupted[m*width + n] - corrupted[j*width + i]) / (2.0*sigma_r*sigma_r)); sum += corrupted[m*width + n] * temp; sum_c += temp; } } sum /= sum_c; if (sum > 255) sum = 255; if (sum < 0) sum = 0; smooth[j*width + i] = sum; } } }
vs2015+opencv3.3.1 实现 c++ 双边滤波器
标签:continue 大小 ace ble size waitkey 复制 ++ sigma
原文地址:http://www.cnblogs.com/goudanli/p/7944929.html