Efficient Path-Based Stereo Matching With Subpixel Accuracy

This paper presents an efficient algorithm to achieve accurate subpixel matchings for calculating correspondences between stereo images based on a path-based matching algorithm. Compared with point-by-point stereo-matching algorithms, path-based algorithms resolve local ambiguities by maximizing the cross correlation (or other measurements) along a path, which can be implemented efficiently using dynamic programming. An effect of the global matching criterion is that cross correlations at all pixels contribute to the criterion; since cross correlation can change significantly even with subpixel changes, to achieve subpixel accuracy, it is no longer sufficient to first find the path that maximizes the criterion at integer pixel locations and then refine to subpixel accuracy. In this paper, by writing bilinear interpolation using integral images, we show that cross correlations at all subpixel locations can be computed efficiently and, thus, lead to a subpixel accuracy path-based matching algorithm. Our results show the feasibility of the method and illustrate significant improvement over existing path-based matching methods.