Stereo Matching Based on Efficient Image-Guided Cost Aggregation
Yunlong Zhan, Yuzhang Gu, Xiaolin Zhang, Lei Qu, Jiatian Pi, Xiaoxia Huang, Yingguan Wang, Jufeng Luo, Yunzhou Qiu · IEICE Transactions on Information and Systems · 2016
Cost aggregation is one of the most important steps in local stereo matching, while it is difficult to fulfill both accuracy and speed. In this letter, a novel cost aggregation, consisting of guidance image, fast aggregation function and simplified scan-line optimization, is developed. Experiments demonstrate that the proposed algorithm has competitive performance compared with the state-of-art aggregation methods on 32 Middlebury stereo datasets in both accuracy and speed.