Hybrid scheme for accurate stereo matching

Stereo matching is a key technique in the field of 3D image and video processing and it plays an important role in a practical stereo vision system. Though stereo matching has been extensively studied and many techniques have been proposed, accurate and efficient stereo matching is still challenging and this issue is worthy of being further studied. In this paper, a novel stereo matching scheme is proposed by jointly exploiting segmentation information, disparity continuity constraints as well as the adaptive support-weight (ASW) technique aiming to acquire efficient and accurate matching results. The proposed scheme consists of two major steps, initial matching and disparity refinement. In the initial matching step, both the reference image and the target image are segmented followed by WTA-based matching, where a new matching cost is developed by jointly exploiting segmentation information, disparity continuity constraints as well as the ASW techniques. Compared with the original one in ASW, ours can reduce the errors in depth discontinuities, repetitive patterns and low texture regions effectively and improve the matching accuracy significantly. In the disparity refinement step, an effective comprehensive refinement scheme is designed by performing measures of occlusion detection, boundary disparity initialization, disparity plane fitting, outlier suppression and discontinuity amendment, which can further correct matching errors and improve the matching accuracy effectively. Experiments are conducted and the results show that the proposed scheme can acquire satisfactory results and outperforms most of the existing methods.