An Improved Adaptive Support-weight Stereo Matching Algorithm with Sparse Region
LU Di;LIN Xue;School of Electrical and Electric Engineering,Harbin University of Science and Technology;
Stereo matching is to obtain disparity map from two or more images whose pixels show disparity between each other. Because adaptive support-weight algorithm is difficult to meet both accuracy and speed,an improved adaptive support-weight sparse region approach based on HVS( human visual system) is proposed. First,we improve the traditional support-weight formula,and the support-weight of the points can be calculated according to the improved support-weight formula. Second,the dense disparity map is obtained by using sparse region-based matching. Third,left-right consistency check and blocking filling is performed for the obtained disparity map. Finally,median filter is used to remove isolated mismatching points and noise points. Experiment results show that,by using the presented method,the matching efficiency is above 90 times faster than that of the adaptive support-weight algorithm proposed by Yoon,and the matching accuracy is 12. 34% higher than that of SSD,so the improved algorithm is verified for obtaining accurate disparity map at a fast pace and meeting the requirements of system practicability.
【CateGory Index】： TP391.41