摘要
立体匹配是双目立体视觉中的核心步骤之一.在户外场景中,传统的立体匹配算法难以达到较高的匹配精度,并且边缘设备既要低成本又要高效率.针对实际应用中存在的上述问题,提出了一种改进的半全局立体匹配算法.首先,整体采用分层迭代的匹配策略,减少计算复杂度的同时可以提高立体匹配精度.其次,使用改进的代价计算方式使得初始代价更为准确.最后,使用并行优化加速计算.实验结果表明,该算法在KITTI2012和KITTI2015数据集上的误匹配率可以达到4.72%和6.04%,使用分辨率为1800×1500的图像测试效率,在256视差条件下,完全优化后的算法时间效率可以提高23.6倍.该算法可有效提高边缘CPU设备的立体匹配效率,并且视差图的误匹配率可以达到主流经典算法的水平.
Stereo matching is one of the core steps in binocular stereo vision.In outdoor scenes,the traditional stereo matching algorithm is difficult to achieve high matching accuracy,and edge computing equipment must be both low-cost and high-efficiency.An improved semi-global stereo matching algorithm is proposed to solve these problems.First of all,a hierarchical iterative matching strategy is adopted as a whole,and reduce the computational complexity.Secondly,using an improved cost calculation method makes the initial cost more accurate.Finally,use parallel optimization to speed up the calculation.Experimental results show that the error matching rate of the proposed algorithm can reach 4.72%and 6.04%on KITTI2012 and KITTI2015 datasets.Use the image resolution of 1800×1500 to test the efficiency,the time efficiency of the fully optimized algorithm can be increased by 23.6 times under 256 disparities conditions.The algorithm can effectively improve the efficiency of stereo matching of edge CPU devices,and the error matching rate of the disparity map can reach the level of mainstream classic algorithms.
作者
陶洋
田家旺
TAO Yang;TIAN Jia-wang(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
出处
《小型微型计算机系统》
CSCD
北大核心
2023年第9期2052-2058,共7页
Journal of Chinese Computer Systems
基金
国家重点研发计划项目(2019YFB2102001)资助
重庆市技术创新与应用发展专项项目(cstc2020jscx-msxmX0178)资助.
