图像配准找到特征点后,怎么对两幅图像的重叠部分对齐融合?已经写好了如下程序,怎么写下去
#include<iostream>
#include <opencv2/opencv.hpp>
#include<string.h>
#include <stdio.h>
#include <opencv2/nonfree/features2d.hpp>
using namespace cv;
using namespace std;
int main(int argc, char* argv[])
{
/*Mat img1=imread("Image01.jpg");*/
Mat img1=imread("1.jpg");
/*Mat img2=imread("Image02.jpg");*/
Mat img2=imread("2.jpg");
//cvtColor(img1,img1,CV_RGB2GRAY);
//cvtColor(img2,img2,CV_RGB2GRAY);
//-- Step 1: Detect the keypoints using SURF Detector检测关键点
int minHessian=400;
SurfFeatureDetector detector( minHessian );
std::vector<KeyPoint> keypoints_1, keypoints_2;//向量类
detector.detect( img1, keypoints_1 );
detector.detect( img2, keypoints_2 );
//-- Step 2: Calculate descriptors (feature vectors)计算描述子
SurfDescriptorExtractor extractor;
Mat descriptors_1, descriptors_2;//两个矩阵
extractor.compute( img1, keypoints_1, descriptors_1 );//把图一的关键点放在描述子这个矩阵中?
extractor.compute( img2, keypoints_2, descriptors_2 );
//-- Step 3: Matching descriptor vectors using FLANN matcher使用FLANN匹配器匹配描述子向量
FlannBasedMatcher matcher;
// BruteForceMatcher<L2<float>> matcher;
std::vector< DMatch > matches;//匹配点(向量)?
matcher.match( descriptors_1, descriptors_2, matches );//把匹配的描述子……
Mat imgMatches;
drawMatches(img1, keypoints_1, img2, keypoints_2, matches, imgMatches);
namedWindow("Matches");
imshow("Matches", imgMatches);///全部的匹配向量
}