The classical semi-global matching algorithm can't use of the pixels around the points to be matched efficiently in the matching cost aggregation process, which will cause mis-match in the weak texture and occlusion region of the image. To solve this problem, the minimum spanning tree is added to the matching cost aggregation process of semi-global stereo matching algorithm, and the matching cost is calculated by dynamic programming along four paths. Solving the matching cost after aggregation within the maximum allowable range of parallax, Finding the parallax that minimizes the matching cost as the apparent difference of the point to be matched. The experimental results show that the Minimum Spanning Tree can be used to treat the pixels around the matching points efficiently and fully, it overcomes the problem that the semi-global matching algorithm can't make full use of the pixels of the image, compared with the original algorithm, the matching accuracy is higher and the aggregation path of matching cost is reduced from 16 to 4, which improves the matching efficiency.
[1]
H. Hirschmüller.
Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information
,
2005,
CVPR.
[2]
Heiko Hirschmüller,et al.
Evaluation of Cost Functions for Stereo Matching
,
2007,
2007 IEEE Conference on Computer Vision and Pattern Recognition.
[3]
Margrit Gelautz,et al.
Simple but Effective Tree Structures for Dynamic Programming-Based Stereo Matching
,
2008,
VISAPP.
[4]
Pedro F. Felzenszwalb,et al.
Efficient belief propagation for early vision
,
2004,
CVPR 2004.
[5]
Daniel P. Huttenlocher,et al.
Efficient Belief Propagation for Early Vision
,
2004,
Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[6]
Sid Ahmed Fezza,et al.
Fast stereo matching via graph cuts
,
2011,
International Workshop on Systems, Signal Processing and their Applications, WOSSPA.