Semi-global matching based disparity estimate using fast Census transform

The Census transform is very useful in stereo matching algorithms. But the traditional Census transform cost too much computation, and its accuracy and robustness are not satisfying. In this paper, a modified semi-global matching (SGM) algorithm based on the fast Census transform is proposed to improve the quality of the range map and decrease the computation. In addition, we modify the disparity refinement to enhance the quality of the estimated range map. Our experiments show that the proposed method performs better than the original SGM algorithm in terms of the accuracy and the anti-noise capability.