在C++中计算类似图像的偏移/倾斜/旋转

Question

我从同一起始位置同时指向同一方向拍摄了多张图像.然而,仍有一点点偏移,因为拍照时这些相机并不在完全相同的位置.我正在寻找一种方法来计算应用于将一个图像与另一个图像匹配所需的最佳平移/剪切/倾斜/旋转,以便它们(几乎)完美地叠加.

图像采用.raw格式,我一次以16位读取.

我被建议(由我的雇主不是程序员[我是实习生])采取部分源图像(不在边缘)和强力搜索相同大小的部分高数据值的相关性.我希望有一个不那么浪费的算法.

Answer 1

这是一个做你想要的短代码(我使用openCV 2.2):

1. 假设您有2个图像:srcImage,dstImage,并且您想要对齐它们
2. 代码很简单.使用它作为算法的基础.

码:

// Detect special points on each image that can be corresponded    
Ptr<FeatureDetector>  detector = new SurfFeatureDetector(2000);  // Detector for features

vector<KeyPoint> srcFeatures;   // Detected key points on first image
vector<KeyPoint> dstFeatures;
detector->detect(srcImage,srcFeatures);
detector->detect(dstImage,dstFeatures); 

// Extract descriptors of the features
SurfDescriptorExtractor extractor;  
Mat projDescriptors, camDescriptors;
extractor.compute(srcImage,  srcFeatures, srcDescriptors);
extractor.compute(dstImage , dstFeatures, dstDescriptors );

// Match descriptors of 2 images (find pairs of corresponding points)
BruteForceMatcher<L2<float>> matcher;       // Use FlannBasedMatcher matcher. It is better
vector<DMatch> matches;
matcher.match(srcDescriptors, dstDescriptors, matches);     

// Extract pairs of points
vector<int> pairOfsrcKP(matches.size()), pairOfdstKP(matches.size());
for( size_t i = 0; i < matches.size(); i++ ){
    pairOfsrcKP[i] = matches[i].queryIdx;
    pairOfdstKP[i] = matches[i].trainIdx;
}

vector<Point2f> sPoints; KeyPoint::convert(srcFeatures, sPoints,pairOfsrcKP);
vector<Point2f> dPoints; KeyPoint::convert(dstFeatures, dPoints,pairOfdstKP);

// Matched pairs of 2D points. Those pairs will be used to calculate homography
Mat src2Dfeatures;
Mat dst2Dfeatures;
Mat(sPoints).copyTo(src2Dfeatures);
Mat(dPoints).copyTo(dst2Dfeatures);

// Calculate homography
vector<uchar> outlierMask;
Mat H;
H = findHomography( src2Dfeatures, dst2Dfeatures, outlierMask, RANSAC, 3);

// Show the result (only for debug)
if (debug){
   Mat outimg;
   drawMatches(srcImage, srcFeatures,dstImage, dstFeatures, matches, outimg, Scalar::all(-1), Scalar::all(-1),
               reinterpret_cast<const vector<char>&> (outlierMask));
   imshow("Matches: Src image (left) to dst (right)", outimg);
   cvWaitKey(0);
}

// Now you have the resulting homography. I mean that:  H(srcImage) is alligned to dstImage. Apply H using the below code
Mat AlignedSrcImage;
warpPerspective(srcImage,AlignedSrcImage,H,dstImage.Size(),INTER_LINEAR,BORDER_CONSTANT);
Mat AlignedDstImageToSrc;
warpPerspective(dstImage,AlignedDstImageToSrc,H.inv(),srcImage.Size(),INTER_LINEAR,BORDER_CONSTANT);