基于Opencv的几种立体匹配算法+ELAS

1、基于Opencv的几种立体匹配算法+ELAS0:ELAS这里要去下载日as的开源库函数。intStereoMatch:ElasMatch()(cv:Matdisp_l,disp_r,disp8u_l,disp8u_r;doubleminVal;doublemaxVal;/视差图的极值cv二MatleftImage=cv二imread(./test_images/leftr31.png,0);cv:MatrightImage=cv二imread(./test_images/rightr31.png,0);/计算视差/generatedisparityimageusingLIBELASintbd=

2、0;constint32_tdims3=leftImage.cols,leftImage.rows,leftImage.cols;cv:Matleftdpf=cv二Mat:zeros(cv二Size(leftImage.cols,leftImage.rows),CV_32F);cv:Matrightdpf=cv:Mat:zeros(cv二Size(leftImage.cols,leftImage.rows),CV_32F);Elas:parametersparam;param.postprocess_only_left=false;Elaselas(param);cess(le

3、ftlmage.data,rightlmage.data,leftdpf.ptr(0),rightdpf.ptr(0),dims);cv二Mat(leftdpf(cv二Rect(bd,0,leftImage.cols,leftImage.rows).copyTo(disp_l);cv二Mat(rightdpf(cv:Rect(bd,0,rightImage.cols,rightImage.rows).copyTo(disp_r);一Checkitsextremevaluescv二minMaxLoc(disp_l,&minVal,&maxVal);coutMindisp:MaxvalueminV

4、almaxVal;numberOfDisparities.=(maxVal-minVal)一DisplayitasaCV_8UC1imagedisp_l.convertTo(disp8u_l,CV_8U,255/(maxVal-minVal);(numberOfDisparities*16.)cv二minMaxLoc(disp_r,&minVal,&maxVal);coutMindisp:MaxvalueminValmaxVal;numberOfDisparities.=(maxVal-minVal)/-DisplayitasaCV_8UC1imagedisp_r.convertTo(disp

5、8u_r,CV_8U,255/(maxVal-minVal);/(numberOfDisparities*16.)cv:normalize(disp8u_l,disp8u_l,0,255,CV_MINMAX,CV_8UC1);/obtainnormalizedimagecv:normalize(disp8u_r,disp8u_r,0,255,CV_MINMAX,CV_8UC1);/obtainnormalizedimagecv:imshow(Left,leftImage);cv二imshow(Right,rightImage);cv:imshow(Elas_left,disp8u_l);cv:

6、imshow(Elas_right,disp8u_r);cv:imwrite(Elas_left.png,disp8u_l);cv:imwrite(Elas_right.png,disp8u_r);coutendlOverendl;cv:waitKey(0);return0;1:BM算法intStereoMatch:BMMatching()cv:Matdisp,disp8u;doubleminVal;doublemaxVal;/视差图的极值cv:Matleftlmage=cv:imread(./test_images/leftr.png,0);cv:MatrightImage=cv二imrea

7、d(./test_images/rightr.png,0);intSADWindowSize=19;intnumberOfDisparities=16*3;/*0?numberOfDisparities:(leftImage.cols/8)+15)&-16;/bm.state-roi1=remapMat.Calib_Roi_L;/左右视图的有效像素区域，一般由双目校正阶段的cvStereoRectify函数传递，也可以自行设定。/bm.state-roi2=remapMat.Calib_Roi_R;/一旦在状态参数中设定了roi1和roi2,OpenCV会通过cvGetValidDispari

8、tyROI函数计算出视差图的有效区域，在有效区域外的视差值将被清零。/bm.State-preFilterSize=41;/预处理滤波器窗口大小，5-21,oddbm.state-preFilterCap=31;/63,1-31/预处理滤波器的截断值，预处理的输出值仅保留卜preFilterCap,preFilterCap范围内的值，bm.state-SADWindowSize=SADWindowSize0?SADWindowSize:9;/SAD窗口大小5-21bm.state-minDisparity=0;/64最小视差，默认值为0bm.state-numberOfDisparities=

9、numberOfDisparities;/128视差窗口，即最大视差值与最小视差值之差，窗口大小必须是16的整数倍bm.state-textureThreshold=10;/低纹理区域的判断阈值。如果当前SAD窗口内所有邻居像素点的x导数绝对值之和小于指定阈值，则该窗口对应的像素点的视差值为0bm.state-uniquenessRatio=15;/5-15视差唯一性百分比，视差窗口范围内最低代价是次低代价的(1+uniquenessRatio/100)倍时，最低代价对应的视差值才是该像素点的视差，否则该像素点的视差为0bm.state-speckleWindowSize=100;/检查视差连

10、通区域变化度的窗口大小，值为0时取消speckle检查bm.state-speckleRange=32;/视差变化阈值，当窗口内视差变化大于阈值时，该窗口内的视差清零bm.state-disp12MaxDiff=1;左视差图(直接计算得出)和右视差图(通过cvValidateDisparity计算得出)之间的最大容许差异。超过该阈值的视差值将被清零。该参数默认为-1,即不执行左右视差检查。注意在程序调试阶段最好保持该值为-1,以便查看不同视差窗口生成的视差效果。/计算视差bm(leftImage,rightImage,disp);/-Checkitsextremevaluescv:minMax

11、Loc(disp,&minVal,&maxVal);coutMindisp:MaxvalueminValmaxVal;/numberOfDisparities.=(maxVal-minVal)/-4.DisplayitasaCV_8UC1imagedisp.convertTo(disp8u,CV_8U,255/(maxVal-minVal);(numberOfDisparities*16.)cv二normalize(disp8u,disp8u,0,255,CV_MINMAX,CV_8UC1);/obtainnormalizedimagecv二imshow(left,leftImage);cv二

12、imshow(right,leftImage);cv二imshow(Disp,disp8u);cv二imwrite(bm.png,disp8u);cv二waitKey(0);2:SGBMintStereoMatch:SGBMMatching()cv二Matdisp,disp8u;doubleminVal;doublemaxVal;/视差图的极值cv二MatleftImage=cv二imread(./test_images/leftr.png,0);cv二MatrightImage=cv二imread(./test_images/rightr.png,0);intnumberOfDisparit

13、ies=16*2;/*0?numberOfDisparities:(leftImage.cols/8)+15)&-16;intSADWindowSize=11;sgbm.preFilterCap=63;sgbm.SADWindowSize=SADWindowSize0?SADWindowSize:3;/3-11intcn=leftImage.channels();sgbm.P1=8*cn*sgbm.SADWindowSize*sgbm.SADWindowSize;P1、P2的值越大，视差越平，toP2P1,可取(50,800)或者(40,2500)sgbm.P2=32*cn*sgbm.SADW

14、indowSize*sgbm.SADWindowSize;sgbm.minDisparity=0;sgbm.numberOfDisparities=numberOfDisparities;128,256sgbm.uniquenessRatio=10;/10,0sgbm.speckleWindowSize=100;/200sgbm.speckleRange=32;sgbm.disp12MaxDiff=1;sgbm.fullDP=1;/计算视差sgbm(leftImage,rightImage,disp);/-Checkitsextremevaluescv二minMaxLoc(disp,&minV

15、al,&maxVal);coutMindisp:MaxvalueminValmaxVal;/numberOfDisparities.=(maxVal-minVal)/-4.DisplayitasaCV_8UC1imagedisp.convertTo(disp8u,CV_8U,255/(maxVal-minVal);/(numberOfDisparities*16.)cv二normalize(disp8u,disp8u,0,255,CV_MINMAX,CV_8UC1);/obtainnormalizedimagecv二imshow(left,leftImage);cv二imshow(right,

16、leftImage);cv二imshow(Disp,disp8u);cv二imwrite(sgbm.png,disp8u);cv二waitKey(0);3:VARintStereoMatch:VARMatching()(cv:Matdisp,disp8u;doubleminVal;doublemaxVal;/视差图的极值cv二MatleftImage=cv二imread(./test_images/leftr.png,0);cv:MatrightImage=cv二imread(./test_images/rightr.png,0);intnumberOfDisparities=16*2;/*0

17、?numberOfDisparities:(leftImage.cols/8)+15)&-16;var.levels=3;/ignoredwithUSE_AUTO_PARAMSvar.pyrScale=0.5;/ignoredwithUSE_AUTO_PARAMSvar.nIt=25;var.minDisp=-numberOfDisparities;var.maxDisp=0;var.poly_n=3;var.poly_sigma=0.0;var.fi=15.0f;var.lambda=0.03f;var.penalization=var.PENALIZATION_TICHONOV;/igno

18、redwithUSE_AUTO_PARAMSvar.cycle=var.CYCLE_V;/ignoredwithUSE_AUTO_PARAMSvar.flags=var.USE_SMART_ID|var.USE_AUTO_PARAMS|var.USE_INITIAL_DISPARITY|var.USE_MEDIAN_FILTERING;/计算视差var(leftImage,rightimage,disp);/-Checkitsextremevaluescv二minMaxLoc(disp,&minVal,&maxVal);coutMindisp:MaxvalueminValendldepth,1

19、);IplImage*right_disp_=cvCreateImage(cvGetSize(leftImage),leftImage-depth,1);cvFindStereoCorrespondenceGC(leftImage,rightImage,left_disp_,right_disp_,state,0);cvReleaseStereoGCState(&state);cvNamedWindow(Left,1);cvNamedWindow(Right,1);cvNamedWindow(GC_left,1);cvNamedWindow(GC_right,1);cvShowImage(Le

20、ft,leftImage);cvShowImage(Right,rightImage);cvNormalize(left_disp_,left_disp_,0,255,CV_MINMAX,CV_8UC1);cvNormalize(right_disp_,right_disp_,0,255,CV_MINMAX,CV_8UC1);cvShowImage(GC_left,left_disp_);cvShowImage(GC_right,right_disp_);cvSaveImage(GC_left.png,left_disp_);cvSaveImage(GC_right.png,right_dis

21、p_);coutendlOverendl;cvWaitKey(O);cvDestroyAllWindows();cvReleaseImage(&leftImage);cvReleaseImage(&rightImage);return0;intStereoMatch:GCMatching_Mat()(doubleminVal;doublemaxVal;/视差图的极值cv:Matdisp8u_l,disp8u_r;cv:MatleftImage=cv二imread(./test_images/leftr31.png,0);cv:MatrightImage=cv二imread(./test_ima

22、ges/rightr31.png,0);CvStereoGCState*state=cvCreateStereoGCState(16,5);cv二Matleft_disp_=leftImage.clone();cv:Matright_disp_=rightImage.clone();IplImagetemp=(IplImage)leftImage;IplImage*leftimg=&temp;IplImagetemp1=(IplImage)rightImage;IplImage*rightimg=&temp1;IplImagetemp2=(IplImage)left_disp_;IplImage*leftdisp=&temp2;IplImagetemp3=(IplImage)right_disp_;IplImage*rightdisp=&temp3;cvFindStereoCorrespondenceGC(leftimg,rightimg,leftdisp,rightdisp,state,0);cvReleaseStereoGCState(&state);cv二namedWindow(Left,1);cv:namedWindow(Right,1);cv:nam