Research Article
Stereo Matching Based on Improved Matching Cost Calculation and Weighted Guided Filtering
@INPROCEEDINGS{10.1007/978-3-030-67720-6_34, author={Junxing Xu and Wei He and Zengshan Tian}, title={Stereo Matching Based on Improved Matching Cost Calculation and Weighted Guided Filtering}, proceedings={Communications and Networking. 15th EAI International Conference, ChinaCom 2020, Shanghai, China, November 20-21, 2020, Proceedings}, proceedings_a={CHINACOM}, year={2021}, month={2}, keywords={Census transform Adaptive window Kirsch operator Weighted guided filtering}, doi={10.1007/978-3-030-67720-6_34} }- Junxing Xu
Wei He
Zengshan Tian
Year: 2021
Stereo Matching Based on Improved Matching Cost Calculation and Weighted Guided Filtering
CHINACOM
Springer
DOI: 10.1007/978-3-030-67720-6_34
Abstract
Aiming at the problem that the existing local stereo matching algorithm has low matching accuracy in weak texture, disparity discontinuity and occlusion regions, an improved algorithm based on matching cost calculation and weighted guided filtering is proposed. The algorithm first improves the traditional gradient cost (GRAD) and Census transform, normalizes and fuses these two matching costs to form a new matching cost, then proposes a weighted guided filter based on the Kirsch operator and aggregates the matching cost, finally, the method of the winner-takes-all (WTA) is used to complete the disparity calculation, and we use the method of left and right disparity consistency and the quadratic curve interpolation to complete the disparity optimization and obtain the final disparity map. A large number of experiments prove that the proposed stereo matching algorithm has an average mismatch rate of about 5.45% relative to the standard disparity map on the test platform of Middlebury. Compared with most algorithms, proposed algorithm achieves a good matching effect.
