双线性插值.rar_sub-pixel_亚像素_双线性插值_插值亚像素

#include <iostream> #include <opencv2/opencv.hpp> #include <opencv2/highgui/highgui.hpp> #include <opencv2/imgproc/imgproc.hpp> #include <stdlib.h> #include <stdio.h> using namespace std; using namespace cv; #define N 25 struct data { Point2d * point; double * left_gray; size_t n; }; double Interpolate(Mat mask, double sx,double sy) { double pixel=0; uchar* data = mask.data; int lRow = static_cast<int>(sy); //最临近行，取整 int nRow = lRow + 1; int lCol = static_cast<int>(sx); //最临近列，取整 int nCol = lCol + 1; double u = (sy - lRow) * 2048; double v = (sx - lCol) * 2048; for (int i = 0; i < mask.rows; i++) { for (int j = 0; j < mask.cols; j++) { pixel = ((2048 - u)*(2048 - v)*data[lRow*mask.step[0] + lCol*mask.step[1]] + (2048 - u)*v*data[lRow * mask.step[0] + nCol * mask.step[1]] + u*(2048 - v)*data[nRow * mask.step[0] + lCol * mask.step[1]] + u*v*data[nRow * mask.step[0] + nCol * mask.step[1]]) / 4194304; } } return pixel; } int main() { double keypointx = 2749.27; double keypointy = 1642; Point2d point[N]; double left_gray[N]; const size_t n = 25; struct data fit_data = { point, left_gray, n }; Mat left = imread("rectifyImageL02.jpg", 0); Mat right = imread("rectifyImageR02.jpg", 0); size_t i; //this is the data to be fitted for (i = 0; i < 5; i++) { point[i].x = keypointx + i - 2; point[i].y = keypointy - 2; point[i+5].x = keypointx + i - 2; point[i+5].y = keypointy - 1; point[i+10].x = keypointx + i - 2; point[i+10].y = keypointy ; point[i+15].x = keypointx + i - 2; point[i+15].y = keypointy + 1; point[i + 20].x = keypointx + i - 2; point[i + 20].y = keypointy + 2; } double a1 = 0.0; double a2 = 0.0; double a3 = 0.0; double a4 = 0.0; double a5 = -506.25; double a6 = 1.17; for (i = 0; i < 25; i++) { double x1i = point[i].x; double y1i = point[i].y; double x2i = (1 + a1)*x1i + a3*y1i + a5; double y2i = a2*x1i + (1 + a4)*y1i + a6; //x方向的近似导数，卷积运算 double Gxi = Interpolate(right, x2i + 1, y2i - 1) + 2 * Interpolate(right, x2i + 1, y2i) + Interpolate(right, x2i + 1, y2i + 1) - Interpolate(right, x2i - 1, y2i - 1) - 2 * Interpolate(right, x2i - 1, y2i) - Interpolate(right, x2i - 1, y2i + 1); //y方向的近似导数,卷积运算 double Gyi = Interpolate(right, x2i - 1, y2i - 1) + 2 * Interpolate(right, x2i, y2i - 1) + Interpolate(right, x2i + 1, y2i - 1) - Interpolate(right, x2i - 1, y2i + 1) - 2 * Interpolate(right, x2i, y2i + 1) - Interpolate(right, x2i + 1, y2i + 1); cout << Gxi << " " << Gyi << endl; cout << " " << endl; } return 0; }