华东理工大学学报（自然科学版）2017，Vol.43Issue(5)：677-683,7.DOI:10.14135/j.cnki.1006-3080.2017.05.012
一种基于多邻域非线性扩散的动态规划全局立体匹配算法
A Dynamic Programming Global Stereo Matching Algorithm Based on Multiple Neighbors' Nonlinear Diffusion
摘要
Abstract
Binocular stereo matching can obtain the accuracy and dense disparity map by comparing two images.However,the utilization of dynamic programming algorithms may result in some shortcomings,such as stripe-like and low accuracy.Aiming these problems,this paper proposes a new stereo matching algorithm based on multiple neighbors' nonlinear diffusion.Firstly,absolute difference test method is used to build disparity space image in raw costs computation period.And then,according to the constraint relation between rows and columns,multiple neighbors' nonlinear diffusion of costs aggregation is proposed to improve the global costs function.Finally,dense disparity maps during the global optimization process are obtained by the edges-optimized DP optimization.The experiment results via Middlebury test images show that the proposed algorithm attains the average PBM 5.60％ and raises the accuracy 39.9％ than IIDP.Moreover,the problem of stripe-like is well solved and the edge-blurring is also improved.Compared with other global matching methods,the proposed algorithm reduces PBM by 38.2％ and has 9 of 11 indexes to rank the first.关键词
动态规划/立体匹配/非线性扩散/视差/代价叠加Key words
dynamic programming/stereo matching/nonlinear diffusion/disparity/costs aggregation分类
信息技术与安全科学引用本文复制引用
耿冬冬,罗娜..一种基于多邻域非线性扩散的动态规划全局立体匹配算法[J].华东理工大学学报（自然科学版）,2017,43(5):677-683,7.基金项目
国家自然科学基金(61403140) （61403140）
上海市自然科学基金(13ZR1411500) （13ZR1411500）
