Local stereo matching with adaptive support-weight, rank transform and disparity calibration

In this paper, a new window-based method for stereo matching is proposed. Differing with the existing local approaches, our algorithm divides the matching process into two steps, initial matching and disparity calibration. Initial disparity is first approximated by an adaptive support-weight and a rank transform method, and then a compact disparity calibration approach is designed to refine the initial disparity, so an accurate result can be acquired. The experimental results are evaluated on the Middlebury dataset, showing that our method is better than other local methods on standard stereo benchmarks.