Multi-cost fusion stereo matching algorithm based on guided filter aggregation

Jingwen Liu; Xuedong Zhang

doi:10.1117/12.2671218

28 April 2023 Multi-cost fusion stereo matching algorithm based on guided filter aggregation

Jingwen Liu, Xuedong Zhang

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126105C (2023) https://doi.org/10.1117/12.2671218
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Aiming at the low matching accuracy of existing local stereo matching algorithms in weak texture areas, a local stereo matching algorithm based on multi-matching cost fusion and guided filtering cost aggregation with adaptive parameters is proposed. First, use the gradient direction to improve the gradient cost, and calculate the matching cost by combining the gradient cost with the Census transform and color cost. Secondly, the cost is aggregated by the guided filtering of adaptive parameters; Finally, the final disparity map is obtained through disparity calculation and multi-step disparity refinement. The improved algorithm is tested on 15 training sets on the Middlebury3 platform, and the average false matching rates of bad4.0 in all areas and non-occluded areas are 19.9% and 13.2%, respectively, which is improved compared with AD-Census and other algorithms.

Citation Download Citation

Jingwen Liu and Xuedong Zhang "Multi-cost fusion stereo matching algorithm based on guided filter aggregation", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126105C (28 April 2023); https://doi.org/10.1117/12.2671218

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