我正在 OpenCV（全景图）中进行图像拼接，但我有一个问题。
我不能使用 OpenCV 中的 Stitching 类，所以我必须只使用特征点和单应性来创建它。
OrbFeatureDetector detector( minHessian );
std::vector<KeyPoint> keypoints_1, keypoints_2;
Mat descriptors_1a, descriptors_2a;
detector.detect( img_1, keypoints_1 , descriptors_1a);
detector.detect( img_2, keypoints_2 , descriptors_2a);
//-- Step 2: Calculate descriptors (feature vectors)
OrbDescriptorExtractor extractor;
Mat descriptors_1, descriptors_2;
cout<<"La distancia es " <<endl;
extractor.compute( img_1, keypoints_1, descriptors_1 );
extractor.compute( img_2, keypoints_2, descriptors_2 );
//-- Step 3: Matching descriptor vectors with a brute force matcher
BFMatcher matcher(NORM_HAMMING, true);
std::vector< DMatch > matches;
matcher.match( descriptors_1, descriptors_2, matches );
在这里我获得了匹配中的特征点，但我需要对其进行过滤：
double max_dist = 0; double min_dist = 100;
//-- Quick calculation of max and min distances between keypoints
for( int i = 0; i < matches.size(); i++ )
{
double dist = matches[i].distance;
//cout<<"La distancia es " << i<<endl;
if( dist < min_dist && dist >3)
{
min_dist = dist;
}
if( dist > max_dist) max_dist = 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 < matches.size(); i++ )
{
//cout<<matches[i].distance<<endl;
if( matches[i].distance < 3*min_dist && matches[i].distance > 3)
{
good_matches.push_back( matches[i]); }
}
现在，我计算单应性
vector<Point2f> p1, p2;
for (unsigned int i = 0; i < matches.size(); i++) {
p1.push_back(keypoints_1[matches[i].queryIdx].pt);
p2.push_back(keypoints_2[matches[i].trainIdx].pt);
}
// Homografía
vector<unsigned char> match_mask;
Mat h = findHomography(Mat(p1),Mat(p2), match_mask,CV_RANSAC);
最后，获取变换矩阵并应用warpPerspective得到两个图像的连接，但我的问题是在最终图像中，照片周围出现黑色区域，当我再次循环时，最终图像将难以辨认。
// Transformar perspectiva para imagen 2
vector<Point2f> cuatroPuntos;
cuatroPuntos.push_back(Point2f (0,0));
cuatroPuntos.push_back(Point2f (img_1.size().width,0));
cuatroPuntos.push_back(Point2f (0, img_1.size().height));
cuatroPuntos.push_back(Point2f (img_1.size().width, img_1.size().height));
Mat MDestino;
perspectiveTransform(Mat(cuatroPuntos), MDestino, h);
// Calcular esquinas de imagen 2
double min_x, min_y, tam_x, tam_y;
float min_x1, min_x2, min_y1, min_y2, max_x1, max_x2, max_y1, max_y2;
min_x1 = min(MDestino.at<Point2f>(0).x, MDestino.at<Point2f>(1).x);
min_x2 = min(MDestino.at<Point2f>(2).x, MDestino.at<Point2f>(3).x);
min_y1 = min(MDestino.at<Point2f>(0).y, MDestino.at<Point2f>(1).y);
min_y2 = min(MDestino.at<Point2f>(2).y, MDestino.at<Point2f>(3).y);
max_x1 = max(MDestino.at<Point2f>(0).x, MDestino.at<Point2f>(1).x);
max_x2 = max(MDestino.at<Point2f>(2).x, MDestino.at<Point2f>(3).x);
max_y1 = max(MDestino.at<Point2f>(0).y, MDestino.at<Point2f>(1).y);
max_y2 = max(MDestino.at<Point2f>(2).y, MDestino.at<Point2f>(3).y);
min_x = min(min_x1, min_x2);
min_y = min(min_y1, min_y2);
tam_x = max(max_x1, max_x2);
tam_y = max(max_y1, max_y2);
// Matriz de transformación
Mat Htr = Mat::eye(3,3,CV_64F);
if (min_x < 0){
tam_x = img_2.size().width - min_x;
Htr.at<double>(0,2)= -min_x;
}
if (min_y < 0){
tam_y = img_2.size().height - min_y;
Htr.at<double>(1,2)= -min_y;
}
// Construir panorama
Mat Panorama;
Panorama = Mat(Size(tam_x,tam_y), CV_32F);
warpPerspective(img_2, Panorama, Htr, Panorama.size(), INTER_LINEAR, BORDER_CONSTANT, 0);
warpPerspective(img_1, Panorama, (Htr*h), Panorama.size(), INTER_LINEAR, BORDER_TRANSPARENT,0);
任何人都知道我怎样才能消除这个黑色区域？是不是我做的不好？任何人都知道我可以看到比较它的功能代码？
谢谢你的时间
编辑：
那是我的形象：
我想消除黑色部分。