立体匹配算法
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立体匹配算法最新动态：
http://vision.middlebury.edu/stereo/eval/
http://www.cvlibs.net/datasets/kitti/eval_stereo_flow.php?benchmark=stereo
相关文献：http://blog.csdn.net/xuyuhua1985/article/details/26283389
介绍立体匹配的基本原理: http://vision.deis.unibo.it/~smatt/Seminars/StereoVision.pdf（比较清晰）
立体匹配综述性文章 ： http://wenku.baidu.com/view/5b359d7d5acfa1c7aa00cc7b.html
立体匹配算法的基本目标：找出图像的每个像素点在另一个视角的图像上对应的像素点，算出视差图像，估算出景深图像。
最简单的SAD块匹配算法
//Stereo Match By SAD #include <opencv2/opencv.hpp> #include <vector> #include <algorithm> #include <iostream> #include <windows.h> #include <string> using namespace std; using namespace cv; DWORD t1; DWORD t2; void timebegin() { t1 = GetTickCount(); } void timeend(string str) { t2 = GetTickCount(); cout << str << " is "<< (t2 - t1)/1000 << "s" << endl; } float sadvalue(const Mat &src1, const Mat &src2) { Mat matdiff = cv::abs(src1 -src2); int saddiff = cv::sum(matdiff)[0]; return saddiff; } float GetMinSadIndex(std::vector<float> &sad) { float minsad = sad[0]; int index = 0; int len = sad.size(); for (int i = 1; i < len; ++i) { if (sad[i] < minsad) { minsad = sad[i]; index = i; } } return index; } void MatDataNormal(const Mat &src, Mat &dst) { normalize(src, dst, 255, 0, NORM_MINMAX ); dst.convertTo(dst, CV_8UC1); } void GetPointDepthRight(Mat &disparity, const Mat &leftimg, const Mat &rightimg, const int MaxDisparity, const int winsize) { int row = leftimg.rows; int col = leftimg.cols; if (leftimg.channels() == 3 && rightimg.channels() == 3) { cvtColor(leftimg, leftimg, CV_BGR2GRAY); cvtColor(rightimg, rightimg, CV_BGR2GRAY); } //Mat disparity = Mat ::zeros(row,col, CV_32S); int w = winsize; int rowrange = row - w; int colrange = col - w - MaxDisparity; for (int i = w; i < rowrange; ++i) { int *ptr = disparity.ptr<int>(i); for (int j = w; j < colrange; ++j) { //Rect rightrect; Mat rightwin = rightimg(Range(i - w,i + w + 1),Range(j - w,j + w + 1)); std::vector<float> sad(MaxDisparity); for (int d = j; d < j + MaxDisparity; ++d) { //Rect leftrect; Mat leftwin = leftimg(Range(i - w,i + w + 1),Range(d - w,d + w + 1)); sad[d - j] = sadvalue(leftwin, rightwin); } *(ptr + j) = GetMinSadIndex(sad); } } } void GetPointDepthLeft(Mat &disparity, const Mat &leftimg, const Mat &rightimg, const int MaxDisparity, const int winsize) { int row = leftimg.rows; int col = leftimg.cols; if (leftimg.channels() == 3 && rightimg.channels() == 3) { cvtColor(leftimg, leftimg, CV_BGR2GRAY); cvtColor(rightimg, rightimg, CV_BGR2GRAY); } //Mat disparity = Mat ::zeros(row,col, CV_32S); int w = winsize; int rowrange = row - w; int colrange = col - w; for (int i = w; i < rowrange; ++i) { int *ptr = disparity.ptr<int>(i); for (int j = MaxDisparity + w; j < colrange; ++j) { //Rect leftrect; Mat leftwin = leftimg(Range(i - w,i + w + 1),Range(j - w,j + w + 1)); std::vector<float> sad(MaxDisparity); for (int d = j; d > j - MaxDisparity; --d) { //Rect rightrect; Mat rightwin = rightimg(Range(i - w,i + w + 1),Range(d - w,d + w + 1)); sad[j - d] = sadvalue(leftwin, rightwin); } *(ptr + j) = GetMinSadIndex(sad); } } } //(Left-Right Consistency (LRC) void CrossCheckDiaparity(const Mat &leftdisp, const Mat &rightdisp, Mat &lastdisp, const int MaxDisparity, const int winsize) { int row = leftdisp.rows; int col = rightdisp.cols; int w = winsize; int rowrange = row - w; int colrange = col - MaxDisparity - w; int diffthreshold = 2; for (int i = w; i < row -w; ++i) { const int *ptrleft = leftdisp.ptr<int>(i); const int *ptrright = rightdisp.ptr<int>(i); int *ptrdisp = lastdisp.ptr<int>(i); for (int j = MaxDisparity + w; j < col - MaxDisparity - w; ++j) { int leftvalue = *(ptrleft + j); int rightvalue = *(ptrright + j - leftvalue ); int diff = abs(leftvalue - rightvalue); if (diff > diffthreshold) { *(ptrdisp + j) = 0; }else { *(ptrdisp + j) = leftvalue; } } } } int main() { Mat leftimg = imread("left1.png",0); Mat rightimg = imread("right1.png",0); if (leftimg.channels() == 3 && rightimg.channels() == 3) { cvtColor(leftimg, leftimg, CV_BGR2GRAY); cvtColor(rightimg, rightimg, CV_BGR2GRAY); } float scale = 1; int row = leftimg.rows * scale; int col = leftimg.cols * scale; resize(leftimg, leftimg, Size( col, row)); resize(rightimg,rightimg, Size(col, row)); Mat depthleft = Mat ::zeros(row,col, CV_32S); Mat depthright = Mat ::zeros(row,col, CV_32S); Mat lastdisp = Mat ::zeros(row,col, CV_32S); int MaxDisparity = 60 * scale; int winsize = 31*scale; timebegin(); GetPointDepthLeft(depthleft, leftimg, rightimg, MaxDisparity, winsize); GetPointDepthRight(depthright, leftimg, rightimg, MaxDisparity, winsize); CrossCheckDiaparity(depthleft,depthright, lastdisp, MaxDisparity, winsize); timeend("time "); MatDataNormal(depthleft,depthleft); MatDataNormal(depthright, depthright); MatDataNormal(lastdisp, lastdisp); namedWindow("left", 0); namedWindow("right", 0); namedWindow("depthleft", 0); namedWindow("depthright", 0); namedWindow("lastdisp",0); imshow("left", leftimg); imshow("right", rightimg); imshow("depthleft", depthleft); imshow("depthright", depthright); imshow("lastdisp",lastdisp); string strsave = "result_"; imwrite(strsave +"depthleft.jpg", depthleft); imwrite(strsave +"depthright.jpg", depthright); imwrite(strsave +"lastdisp.jpg",lastdisp); waitKey(0); return 0; }
left.png right.png
