Joint Bilateral Filter and Multi-Scale Cost Aggregation in Stereo Matching
You-ping Ye, Hong Yuan Zheng, Hao Chen, Yu Yang · 2015
Dense correspondence is a key problem in binocular stereo vision.The existing solution for this problem can be divided into local method and global or semi-global method.Bilaterally weighted patches matching is a classical local method, while it is computationally expensive and its accuracy need to be improved.In this paper, a new method is proposed which uses bilaterally weighted method to calculate matching cost and multi-scale method to produce cost aggregation.Use Gauss down-sampling method to produce multi-scale image, calculate matching cost in every sample scale.Then add inter-scale regularization into optimization function and solve the new optimization problem.This new algorithm is evaluated on Middlebury dataset, and it presents significant improvement than single bilaterally weighted method.