Four-direction global matching with cost volume update for stereovision

The accuracy and speed of semi-global matching (SGM) make it widely used in many computer vision problems. However, SGM often struggles in dealing with pixels in the homogeneous regions and also suffers from streak artefacts for weak smoothness constraints. Meanwhile, we observe that the global method usually fails in occluded areas. The disparities for occluded pixels are typically the average of the disparity of nearby pixels. The local method can propagate the information into occluded pixels with a similar color. In this paper, we propose a novel, to the best of our knowledge, four-direction global matching with a cost volume update scheme to cope with textureless regions and occlusion. The proposed method makes two changes in the recursive formula: a) the computation process considers four visited nodes to enforce more smooth constraints; b) the recursive formula integrates cost filtering to propagate reliable information farther in nontextured regions. Thus, our method can inherit the speed of SGM, properly avoid streaking artefacts, and deal with the occluded pixel. Extensive experiments in stereo matching on Middlebury demonstrate that our method outperforms typical SGM-based cost aggregation approaches and other state-of-the-art local methods.