本文通過攝像頭參數(shù)（fx,fy,cx,cy,k1,k2,p1,p2,p3（標(biāo)定得到））去矯正攝像頭拍出來的圖像畸變

詳細(xì)代碼在底部

首先

這里我們先介紹兩個(gè)函數(shù)：他們都可以用來矯正畸變，但是一個(gè)是輸入是Mat型，一個(gè)輸入是IplImage* 型

本文用Mat格式讀取圖像，故采用第一個(gè)函數(shù)。

undistort()? ? ? ? //用于Mat圖像

cvUndistort()? ? ?//用于 IplImage* 圖像

其次

標(biāo)定一下攝像頭，得到參數(shù)矩陣。（我用matlab標(biāo)定工具箱搞出來的~）

Matlab2019 標(biāo)定工具箱結(jié)果

再次

這里通過paramtersInit()將參數(shù)轉(zhuǎn)換為系數(shù)陣

然后傳入到undistort里面去，這就結(jié)束了~

效果

畸變矯正前/后

代碼

```

#include <iostream>

#include<opencv2/core/core.hpp>

#include <opencv2/highgui/highgui.hpp>

#include <opencv2/imgproc/imgproc.hpp>

using namespace cv;

using namespace std;

Mat matrix;

Mat coeff;

Mat new_matrix;

double fx = 682.421509, fy = 682.421509, cx = 633.947449, cy = 404.559906;

double k1k2Distortion[2] = {-0.15656,-0.00404};

double p1p2p3Distortion[3] = {-0.00078,-0.00048,0.00000};

using namespace cv;

using namespace std;

void paramtersInit();//將參數(shù)轉(zhuǎn)換為系數(shù)陣

int main()

{

cv::Mat srcMat, dstMat;

paramtersInit();

srcMat = imread("img.jpg");

undistort(srcMat, dstMat, matrix, coeff, new_matrix);

imwrite("undistortImg.png", dstMat);

imshow("front", srcMat);

imshow("after",dstMat);

waitKey(0);

system("pause");

return 0;

}

void paramtersInit()

{

matrix = Mat(3, 3, CV_64F);

matrix.at<double>(0, 0) = fx;

matrix.at<double>(0, 1) = 0;

matrix.at<double>(0, 2) = cx;

matrix.at<double>(1, 0) = 0;

matrix.at<double>(1, 1) = fy;

matrix.at<double>(1, 2) = cy;

matrix.at<double>(2, 0) = 0;

matrix.at<double>(2, 1) = 0;

matrix.at<double>(2, 2) = 1;

coeff = Mat(1, 4, CV_64F);

coeff.at<double>(0, 0) = k1k2Distortion[0];

coeff.at<double>(0, 1) = k1k2Distortion[1];

coeff.at<double>(0, 2) = p1p2p3Distortion[0];

coeff.at<double>(0, 3) = p1p2p3Distortion[1];

}

```