New Stereo Matching Method Based Edge Extraction

Computing disparity images for stereo pairs of low texture images is a challenging task because matching costs inside low texture areas of the stereo pairs are almost similar.This problem can not be solved straightforwardly by increasing the size of aggregation windows or by using global optimization methods,e.g.dynamic programming,because those approaches will smooth depth discontinued boundaries as well.This paper proposes a new method that is able to robustly perform stereo matching for low texture stereo images.First,edge detection and Sobel filtering are performed for the images;second,edge maps is used to guide the aggregation of pixel matching costs;Finally,disparity computation and left-right validation(≥88%) are used to get the disparity maps.Experimental results demonstrate that the proposed method utilizes the edge maps computed from the stereo pairs to guide the cost aggregation process in stereo matching,and can produce a larger number of and a better accuracy of reliable disparities for low texture stereo images than the moving average method.