distort2no_distort

最新推荐文章于 2023-10-29 12:12:31 发布

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最新推荐文章于 2023-10-29 12:12:31 发布

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CC 4.0 BY-SA版权

本文链接：https://blog.youkuaiyun.com/weixin_38378417/article/details/89491464

本文介绍了一种基于OpenCV的畸变校正算法，通过非线性最小化计算，实现图像畸变点到非畸变点的精确映射。算法详细展示了如何利用DownhillSolver进行畸变参数求解，适用于相机畸变校正场景。

#include <iostream>
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include <fstream>
using namespace cv;
using namespace std;
class DistortF :public cv::MinProblemSolver::Function
{
public:
    DistortF(double _distortU, double _distortV) : distortU(_distortU), distortV(_distortV)
    {

        Mat cameraMatrix = (Mat_<double>(3, 3) << 422.47278482, 0., 337.95105539, 0., 421.51185173, 230.2749964, 0., 0., 1.);
        inverseCameraMatrix = (cameraMatrix.colRange(0,3)).inv(DECOMP_LU);

        k1 = -0.36446607;
        k2 = 0.10597863;
        p1 = 0.00088569;
        p2 = -0.00112412;
        k3 = 0.;
        k4 =  0.;
        k5 = 0.;
        k6 = 0.;
        s1 = 0.;
        s2 =  0.;
        s3 = 0.;
        s4 = 0.;
        tauX =  0.;
        tauY =  0.;
    }
    int getDims() const { return 2; }
    double calc(const double* x)const{

        double undistortU = x[0];
        double undistortV = x[1];
        const double* ir = &inverseCameraMatrix(0, 0);
        //cout<< ir[0]<<endl;
        Mat cameraMatrix = (Mat_<double>(3, 3) << 422.47278482, 0, 337.95105539, 0, 421.51185173, 230.2749964, 0, 0, 1);
        const double* pA = (const double*)cameraMatrix.data;

        double Xd = undistortU * ir[0] + undistortV * ir[1] + ir[2], Yd = undistortU * ir[3] + undistortV * ir[4] + ir[5], Wd = undistortU * ir[6] + undistortV * ir[7] + ir[8];
        Wd = 1. / Wd;
        Xd = Xd * Wd;
        Yd = Yd * Wd;

        double Xd_2 = Xd*Xd, Yd_2 = Yd * Yd, r_2 = Xd_2 + Yd_2, _2XdYd = 2 * Xd * Yd;
        double kr = (1 + ((k3*r_2 + k2)*r_2 + k1)*r_2) / (1 + ((k6*r_2 + k5)*r_2 + k4)*r_2);
        double Xdd = (Xd*kr + p1*_2XdYd + p2*(r_2 + 2 * Xd_2) + s1*r_2 + s2*r_2*r_2);;
        double Ydd = (Yd*kr + p1*(r_2 + 2 * Yd_2) + p2*_2XdYd + s3*r_2 + s4*r_2*r_2);
        double Wdd = Wd;

        double distortU_d = pA[0] * Xdd + pA[1] * Ydd + pA[2] * Wdd;
        double distortV_d = pA[3] * Xdd + pA[4] * Ydd + pA[5] * Wdd;
        //printf("%f\n",sqrt((distortU - distortU_d) * (distortU - distortU_d) + (distortV - distortV_d) * (distortV - distortV_d)));
        return sqrt((distortU - distortU_d) * (distortU - distortU_d) + (distortV - distortV_d) * (distortV - distortV_d));
    }
private:
    double distortU, distortV;

    double k1;
    double k2;
    double p1;
    double p2;
    double k3;
    double k4;
    double k5;
    double k6;
    double s1;
    double s2;
    double s3;
    double s4;
    double tauX;
    double tauY;

    Mat_<double> inverseCameraMatrix;
};
string image_file = "images/4433.jpg";
int main() {
    cv::Mat image = cv::imread(image_file,0);   // 图像是灰度图，CV_8UC1
    int rows = image.rows, cols = image.cols;
    cv::Mat image_undistort = cv::Mat(rows, cols, CV_8UC1);
    ofstream oFile;
    oFile.open("/2.csv", ios::out | ios::trunc);
    oFile << "x_distortion" << "," << "y_distortion" << "," << "x_nodistor" << "," << "y_nodistor" << endl;
    for (int v_distorted = 0; v_distorted < rows; v_distorted++)
        for (int u_distorted = 0; u_distorted < cols; u_distorted++) {
            double u = 0, v = 0;
            cv::Ptr<cv::DownhillSolver> solver = cv::DownhillSolver::create();
            cv::Ptr<cv::MinProblemSolver::Function> ptr_F = cv::makePtr<DistortF>(u_distorted, v_distorted);//x,y为有畸变的点
            int lFaliedUndistCount=0;
            cv::Mat solution;
            solution= (cv::Mat_<double>(1, 2) << u_distorted, v_distorted);
            cv::Mat step;
            step= (cv::Mat_<double>(2, 1) << -0.5, -0.5);

            solver->setFunction(ptr_F);
            solver->setInitStep(step);
            float res=solver->minimize(solution);
            // cout<<res<<endl;
            u = solution.at<double>(0, 0);
            v = solution.at<double>(0, 1);
            if (u>= 0 && v >= 0 && u < cols && v < rows) {
                int a=0;
                a=image.at<uchar>((int) v_distorted, (int) u_distorted);
                image_undistort.at<uchar>((int)v, (int)u) =a;
            }
            oFile << u_distorted << "," << v_distorted<< "," << (int)u << "," << (int)v << endl;
        }

    cv::imshow("image undistorted", image_undistort);
    cv::waitKey();
    return  0;
}

对应的cmake.txt

cmake_minimum_required(VERSION 3.10)
project(untitled8)

set(CMAKE_CXX_STANDARD 11)

add_executable(untitled8 main.cpp)
target_link_libraries(untitled8 opencv_core opencv_highgui opencv_imgproc opencv_imgcodecs )

必须opencv3,这个是3.3.0

单个点的：

#include <iostream>
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/videoio.hpp"
#include<time.h>
#define UNDISTORT_FAILED_THRES 0.1
using namespace cv;
using namespace std;
//非线性最小化计算函数
class DistortF :public cv::MinProblemSolver::Function
{
public:
    DistortF(double _distortU, double _distortV) : distortU(_distortU), distortV(_distortV)
    {

        Mat cameraMatrix = (Mat_<double>(3, 3) << 422.47278482, 0., 337.95105539, 0., 421.51185173, 230.2749964, 0., 0., 1.);
        inverseCameraMatrix = (cameraMatrix.colRange(0,3)).inv(DECOMP_LU);

        k1 = -0.36446607;
        k2 = 0.10597863;
        p1 = 0.00088569;
        p2 = -0.00112412;
        k3 = 0.;
        k4 =  0.;
        k5 = 0.;
        k6 = 0.;
        s1 = 0.;
        s2 =  0.;
        s3 = 0.;
        s4 = 0.;
        tauX =  0.;
        tauY =  0.;
    }
    int getDims() const { return 2; }
    double calc(const double* x)const{

        double undistortU = x[0];
        double undistortV = x[1];
        const double* ir = &inverseCameraMatrix(0, 0);
        //cout<< ir[0]<<endl;
        Mat cameraMatrix = (Mat_<double>(3, 3) << 422.47278482, 0, 337.95105539, 0, 421.51185173, 230.2749964, 0, 0, 1);
        const double* pA = (const double*)cameraMatrix.data;

        double Xd = undistortU * ir[0] + undistortV * ir[1] + ir[2], Yd = undistortU * ir[3] + undistortV * ir[4] + ir[5], Wd = undistortU * ir[6] + undistortV * ir[7] + ir[8];
        Wd = 1. / Wd;
        Xd = Xd * Wd;
        Yd = Yd * Wd;

        double Xd_2 = Xd*Xd, Yd_2 = Yd * Yd, r_2 = Xd_2 + Yd_2, _2XdYd = 2 * Xd * Yd;
        double kr = (1 + ((k3*r_2 + k2)*r_2 + k1)*r_2) / (1 + ((k6*r_2 + k5)*r_2 + k4)*r_2);
        double Xdd = (Xd*kr + p1*_2XdYd + p2*(r_2 + 2 * Xd_2) + s1*r_2 + s2*r_2*r_2);;
        double Ydd = (Yd*kr + p1*(r_2 + 2 * Yd_2) + p2*_2XdYd + s3*r_2 + s4*r_2*r_2);
        double Wdd = Wd;

        double distortU_d = pA[0] * Xdd + pA[1] * Ydd + pA[2] * Wdd;
        double distortV_d = pA[3] * Xdd + pA[4] * Ydd + pA[5] * Wdd;
        //printf("%f\n",sqrt((distortU - distortU_d) * (distortU - distortU_d) + (distortV - distortV_d) * (distortV - distortV_d)));
        return sqrt((distortU - distortU_d) * (distortU - distortU_d) + (distortV - distortV_d) * (distortV - distortV_d));
    }
private:
    double distortU, distortV;

    double k1;
    double k2;
    double p1;
    double p2;
    double k3;
    double k4;
    double k5;
    double k6;
    double s1;
    double s2;
    double s3;
    double s4;
    double tauX;
    double tauY;

    Mat_<double> inverseCameraMatrix;
};
//输入畸变图中的x,y点
int main() {
    double x,y;
    cout << "Input x: ";
    cin >> x;
    cout << "Input y: ";
    cin >> y;
    clock_t start,finish;
    double totaltime;
    start=clock();
    cv::Ptr<cv::DownhillSolver> solver = cv::DownhillSolver::create();
    cv::Ptr<cv::MinProblemSolver::Function> ptr_F = cv::makePtr<DistortF>(x, y);//x,y为有畸变的点
    int lFaliedUndistCount=0;
    cv::Mat solution;
    solution= (cv::Mat_<double>(1, 2) << x, y);
    cv::Mat step;
    step= (cv::Mat_<double>(2, 1) << -0.5, -0.5);

    solver->setFunction(ptr_F);
    solver->setInitStep(step);
    float res=solver->minimize(solution);
    // cout<<res<<endl;
    double u = solution.at<double>(0, 0);
    double v = solution.at<double>(0, 1);
    finish=clock();
    totaltime=(double)(finish-start)/CLOCKS_PER_SEC;
    cout<<"\n此程序的运行时间为"<<totaltime<<"秒！"<<endl;
    cout<<int(u)<<endl;
    cout<<int(v)<<endl;
}