非参数变换和改进动态规划的立体匹配算法

门宇博¹, 马宁^1,2, 张国印¹, 李香¹, 门朝光¹, 孙鹏飞²

(1.哈尔滨工程大学 计算机科学与技术学院, 150001 哈尔滨; 2.哈尔滨师范大学 计算机科学与信息工程学院,150001 哈尔滨)



摘要:

针对传统稠密立体匹配方法在非纹理区、深度不连续处和遮挡处存在错误匹配率过高的问题,提出一种基于非参数变换和改进动态规划相结合的立体匹配算法.采用稀疏非参数变换相关方法计算初始局部匹配代价,并利用行列双向约束动态规划算法对匹配代价进行全局优化,在获取初始视差后分别对原始图像每一像素点进行可信性与纹理性检测,最后利用视差平面拟合结果代替非纹理与非可信区域像素点的原始视差,得到稠密视差图.实验表明,该算法具有较高的鲁棒性与匹配精度,尤其在处理图像的非纹理区、深度不连续处和遮挡处,可获得精确的匹配结果.

关键词:  立体匹配  Census变换  动态规划  双向约束  视觉导航

DOI：10.11918/j.issn.0367-6234.2015.03.010

分类号:TP391.41

基金项目:国家自然科学基金(61100004); 黑龙江省自然科学基金 (F201320).



A stereo matching algorithm based on Census transform and improved dynamic programming

MEN Yubo¹, MA Ning^1,2, ZHANG Guoyin¹, LI Xiang¹, MEN Chaoguang¹, SUN Pengfei²

(1.College of Computer Science and Technology, Harbin Engineering University, 150001 Harbin, China; 2. College of Computer Science and Information Engineering, Harbin Normal University, 150001 Harbin, China)

Abstract:

A stereo matching algorithm based on Census transform and improved dynamic programming is proposed to the problems of traditional dense stereo matching methods, which have high false matching rate in the textureless areas, depth discontinuities and occlusion. The initial local matching cost is calculated by sparse Census transform correlation, and the raw cost is also optimized by a dynamic programming method by involvoing bidirectional constraints of row and column simultaneously. Meanwhile, the confidence and texture of each pixel are measured for reference image. Finally, the disparities of non-confident or textureless pixels are estimated by fitting parameters of a plane model for the corresponding segment, and the dense disparity map was obtained as well. Experiment results demonstrate that the proposed algorithm achieves high matching accuracy and robustness, especially in the textureless areas, depth discontinuities, and occlusion as well.

Key words:  stereo matching  census transform  dynamic programming  bidirectional constraint  vision navigation