void vpTemplateTrackerWarpHomography::pRondp(const vpColVector &p1, const vpColVector &p2,vpColVector &pres) const
{
vpHomography H1 = getHomography(p1);
vpHomography H2 = getHomography(p2);
vpHomography H = H1*H2;
getParam(H,pres);
}
int main() {
clock_t begin = clock();
// CODE
int u = 1125;
cv::Mat thetaMatrix, output;
cv::Mat H = getHomography(image0Points, image1Points);
double theta = atan2(-H.at<double>(2, 1), -H.at<double>(2, 0));
double thetaMatrixTmp[2][2] = {
{cos(theta), -sin(theta)},
{sin(theta), cos(theta)}
};
cv::Mat(2, 2, CV_64F, &thetaMatrixTmp).copyTo(thetaMatrix);
std::cout << "H\n" << H << "\n";
changeHomographyCoords(H, thetaMatrix);
std::cout << "H'\n" << H << "\n";
output = halfProjectiveWarp(H, image1, u, thetaMatrix, true);
// CODE
clock_t end = clock();
double elapsed_secs = double(end - begin) / CLOCKS_PER_SEC;
std::cout << "It took " << elapsed_secs << " seconds\n";
cv::namedWindow("Gray image", CV_WINDOW_AUTOSIZE);
cv::imshow("Gray image", output);
cv::waitKey(0);
imwrite("output.jpg", output);
return 0;
}
void PerspectiveTransform::transform(float t, const cv::Mat& source, cv::Mat& result) const
{
cv::warpPerspective(source, result, getHomography(t, source), source.size(), cv::INTER_CUBIC);
}
int main(int argc,char** argv)
{
const int image_count=10;
cv::Mat Thermal_image[image_count];
cv::Mat RGB_image[image_count];
cv::Mat Homography[image_count];
cv::SparseMat A[image_count];//degrading matrix
int mfactor=2;//magnification factor
std::string Thermal[]= {"43","44","45","46","47","48","49","50","51","52"};
std::string RGB[]= {"T00043VB","T00044VB","T00045VB","T00046VB","T00047VB","T00048VB","T00049VB","T00050VB","T00051VB","T00052VB"};
std::ostringstream Thermal_input[image_count];
std::ostringstream RGB_input[image_count];
for(int n=0; n<image_count; n++)
{
Thermal_input[n]<<"./input/"<<Thermal[n]<<".bmp";
}
for(int n=0; n<image_count; n++)
{
Thermal_image[n]=cv::imread(Thermal_input[n].str());
}
for(int n=0; n<image_count; n++)
{
RGB_input[n]<<"./input/"<<RGB[n]<<".jpg";
}
for(int n=0; n<image_count; n++)
{
RGB_image[n]=cv::imread(RGB_input[n].str());
}
cv::Mat ideal=cv::imread("./input/ideal.bmp");
cv::Mat dst(ideal.rows,ideal.cols,CV_8UC3);
int range=20;
for(int n=0; n<image_count; n++)
{
std::cout<<"image_count="<<n<<std::endl;
//Homography[n]=getHomography(degimage[n],degimage[image_count-1]);
//Homography[n]=getHomography(RGB_image[0],RGB_image[n]);
Homography[n]=getHomography(Thermal_image[0],Thermal_image[n]);
std::cout<<Homography[n]<<std::endl;
if(!n)
{
Homography[n]=(cv::Mat_<float>(3,3)<<1.0f,0.0f,0.0f,0.0f,1.0f,0.0f,0.0f,0.0f,1.0f);
}
A[n]=CreateDegradingMatrix(ideal,mfactor,Homography[n]);
}
int iteration=100;
float beta=1.3f;//convergence speed
//BTV
cv::Size BTVkernel(7,7);
float alpha=0.7f;
float lambda=0.03f;
SuperResolution(Thermal_image,dst,A,image_count,iteration,beta,range,ideal,BTVkernel,alpha,lambda);
}
void vpTemplateTrackerWarpHomography::getParamInverse(const vpColVector &ParamM,vpColVector &ParamMinv) const
{
vpHomography H = getHomography(ParamM);
vpHomography Hinv = H.inverse();
getParam(Hinv, ParamMinv);
}
