Stereo Matching Based on Adaptive Matching Windows and Multi-feature Fusion
SHI Hua1,2, ZHU Hong1
1.School of Automation and Information Engineering, Xi′an University of Technology, Xi′an 710048 2.School of Science, Xi′an Technological University, Xi′an 710032
Abstract：Aiming at the problems of local stereo matching methods, such as difficulties in matching window selection, vague disparity of edges and low accuracy in weak texture regions and slope surface regions, an efficient stereo matching algorithm with adaptive support window based on segmentation in CIELAB color space and multiple features fusion is proposed in this paper. Firstly, the stereo images are segmented in CIELAB color space, the initial support window is calculated according to the homogeneous regions, and the initial support window is updated by estimating the occlusion region. And then the initial disparity map in the updated support region is achieved by the linear weighted multi-feature fusion matching method with adaptive weights. Finally, the mismatch is checked by consistency of right disparity and left disparity, and then the ultimate dense disparity map is obtained through disparity optimization by mean filtering and disparity refinement. Experimental results show that the proposed algorithm is effective with high matching precision, especially for weak texture and slope surface regions.
2016, Vol. 29 
