计算单应性后如何拼接两个图像

Question

我正在尝试在 opencv c++ 中拼接两个重叠的图像。我使用 ORB 进行特征匹配，并计算了两个图像之间的 Homography。现在使用这个 Homography 矩阵我想进一步添加两个图像。但我不知道如何更进一步。谁能告诉我接下来的步骤。 到目前为止我写的代码是：

detector->detect(img1, kp1,descriptors_img1);
detector->detect(img2, kp2,descriptors_img2);


Ptr<DescriptorExtractor> extractor = ORB::create();
extractor->compute(img1, kp1, descriptors_img1 );
extractor->compute(img2, kp2, descriptors_img2 );

if ( descriptors_img1.empty() )
    cvError(0,"MatchFinder","1st descriptor empty",__FILE__,__LINE__);
if ( descriptors_img2.empty() )
    cvError(0,"MatchFinder","2nd descriptor empty",__FILE__,__LINE__);
descriptors_img1.convertTo(descriptors_img1, CV_32F);
descriptors_img2.convertTo(descriptors_img2, CV_32F);
FlannBasedMatcher matcher;
std::vector<DMatch> matches;
matcher.match(descriptors_img1,descriptors_img2,matches);
double max_dist = 0; double min_dist = 100;

//-- Quick calculation of max and min distances between keypoints
for( int i = 0; i < descriptors_img1.rows; i++ )
{
    double dist = matches[i].distance;
    if( dist < min_dist )
        min_dist = dist;
    if( dist > max_dist )
        max_dist = dist;
}

printf("-- Max dist : %f \n", max_dist );
printf("-- Min dist : %f \n", min_dist );

//-- Draw only "good" matches (i.e. whose distance is less than 3*min_dist )
std::vector< DMatch > good_matches;

for( int i = 0; i < descriptors_img1.rows; i++ )
{
    if( matches[i].distance < 3*min_dist )
    {
        good_matches.push_back( matches[i]);
    }
}
Mat img_matches;
drawMatches(img1,kp1,img2,kp2,good_matches,img_matches,Scalar::all(-1),
        Scalar::all(-1),vector<char>(),DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
//-- Localize the object
std::vector<Point2f> obj;
std::vector<Point2f> scene;
for( int i = 0; i < good_matches.size(); i++ )
{
    //-- Get the keypoints from the good matches
    obj.push_back( kp1[ good_matches[i].queryIdx ].pt );
    scene.push_back( kp2[ good_matches[i].trainIdx ].pt );
}

Mat H = findHomography( obj, scene, CV_RANSAC );

Answer 1

计算出单应矩阵后，您只需要将图像变形并将它们混合在一起。这可以使用warpPerspective 函数来完成，如下所示。

cv::Mat result;

warpPerspective( img1, result, H, cv::Size( img1.cols+img2.cols, img1.rows) );
cv::Mat half(result, cv::Rect(0, 0, img2.cols, img2.rows) );
img2.copyTo(half);

结果是您最终拼接的图像。希望这能解决您的问题。