Multi-Resolution Stereo Matching Using Maximum-Surface Techniques

This paper presents a fast and reliable stereo matching algorithm which produces a dense disparity map by using fast cross-correlation, rectangular subregioning and maximumsurface techniques in a coarse-to-fine scheme. Fast correlation is achieved by using the box filtering technique whose speed is invariant to the size of the correlation window, and by segmenting the images at different levels of the pyramid into rectangular subimages. By working with rectangular subimages, the speed of the algorithm can be increased and the intermediate memory storage requirement is reduced. The disparity for the whole image is found in the correlation coefficient volume by obtaining the maximum-surface rather than simply choosing the position that gives the maximum correlation coefficient value. Typical running time for a 512 512 image is in the order of half a minute rather than minutes or hours. A variety of synthetic and real images have been tested, and good results have been obtained.