對OpenCV中涉及的三種立體匹配算法進行代碼及各自優缺點總結:
首先我們看一下BM算法:
該算法代碼:
- CvStereoBMState *BMState = cvCreateStereoBMState();
- int SADWindowSize=15;
- BMState->SADWindowSize = SADWindowSize > 0 ? SADWindowSize : 9;
- BMState->minDisparity = 0;
- BMState->numberOfDisparities = 32;
- BMState->textureThreshold = 10;
- BMState->uniquenessRatio = 15;
- BMState->speckleWindowSize = 100;
- BMState->speckleRange = 32;
- BMState->disp12MaxDiff = 1;
- cvFindStereoCorrespondenceBM( left, right, left_disp_,BMState);
- cvNormalize( left_disp_, left_vdisp, 0, 256, CV_MINMAX );
其中minDisparity是控制匹配搜索的第一個參數,代表了匹配搜蘇從哪裏開始,numberOfDisparities表示最大搜索視差數uniquenessRatio表示匹配功能函數,這三個參數比較重要,可以根據實驗給予參數值。
該方法速度最快,一副320*240的灰度圖匹配時間爲31ms,視差圖如下。
第二種方法是SGBM方法這是opencv的一種新算法:
- cv::StereoSGBM sgbm;
- sgbm.preFilterCap = 63;
- int SADWindowSize=11;
- int cn = 1;
- sgbm.SADWindowSize = SADWindowSize > 0 ? SADWindowSize : 3;
- sgbm.P1 = 4*cn*sgbm.SADWindowSize*sgbm.SADWindowSize;
- sgbm.P2 = 32*cn*sgbm.SADWindowSize*sgbm.SADWindowSize;
- sgbm.minDisparity = 0;
- sgbm.numberOfDisparities = 32;
- sgbm.uniquenessRatio = 10;
- sgbm.speckleWindowSize = 100;
- sgbm.speckleRange = 32;
- sgbm.disp12MaxDiff = 1;
- sgbm(left , right , left_disp_);
- sgbm(right, left , right_disp_);
各參數設置如BM方法,速度比較快,320*240的灰度圖匹配時間爲78ms,視差效果如下圖。
第三種爲GC方法:
- CvStereoGCState* state = cvCreateStereoGCState( 16, 2 );
- left_disp_ =cvCreateMat( left->height,left->width, CV_32F );
- right_disp_ =cvCreateMat( right->height,right->width,CV_32F );
- cvFindStereoCorrespondenceGC( left, right, left_disp_, right_disp_, state, 0 );
- cvReleaseStereoGCState( &state );
該方法速度超慢,但效果超好。