A pixel pair–based encoding pattern for stereo matching via an adaptively weighted cost. Issue 4 (26th December 2020) - Fu, Yuli; Lai, Kaimin; Chen, Weixiang; Xiang, Youjun
Abstract: Stereo matching, which is a key problem in computer vision, faces the challenge of radiometric distortions. Most of the existing stereo matching methods are based on simple matching cost algorithms and appear the problem of mismatch under radiometric distortions. It is necessary to improve the robustness and accuracy of matching cost algorithms. A novel encoding pattern is proposed for stereo matching. In the proposed encoding pattern, each of the matching windows in the grey image and gradient images is divided into several isoline‐like sets with different radii. Then, pixel pairs are defined in the isoline‐like sets. An encoding function is used to decide the relative order between the two pixels in each pixel pair. To apply the pattern for matching cost computation and enhance the matching accuracy, an adaptively weighted cost is designed that is related to the isoline‐like sets. Experiments are conducted on the Middlebury and KITTI data sets to show the validity of the proposed method under severe radiometric distortions. Also, the comparisons with some widely used methods are made in the experiments to illustrate the advantage of the proposed method.