Fast sub-pixel accuracy stereo image matching based on disparity plane

Abstract

To avoid “stair-casing effect” in the disparity map when dealing with slant plane, curved surface and weak texture region, an improved fast dense stereo matching algorithm based on disparity plane estimation is proposed. First, a set of support points are extracted from the edge of the original matching images and the description images. Second, Delaunay triangulation disparity planes are calculated using all the support points. Third, the sub-pixel disparity map is computed from the best support points and parameters of the Delaunay triangulation disparity planes. Finally, experimental results show that the “stair-casing effect” caused by slant plane, curved surface and weak texture region is eliminated by using the presented method. In addition, the proposed method spends less than 600ms on a one-megapixel image averagely.