基于改进Census变换的多特性立体匹配算法

A multi-feature stereo matching algorithm based on improved Census transform

针对当前立体匹配算法存在的匹配准确率低,难以达到实用的高精度水平的问题,提出了一种基于改良的Census变换与色彩信息和梯度测度相结合的多特性立体匹配算法,实现高精度的双目立体匹配。算法首先在初始代价匹配阶段,将改进的Census变换、色彩和梯度测度赋权求和得出可靠的初始匹配代价;在聚合阶段,采取高效快捷的最小生成树聚合,获得匹配代价矩阵;最后根据胜者为王法则得到初始视差图,并引入左右一致性检测等策略优化视差图,获得高精度的视差图,实验阶段对源自Middlebury上的标准测试图进行测试验证,实验结果表明,经本文算法处理得到的15组测试数据集的视差图在非遮挡区域的平均误匹配率为6.81%,算法实时响应性优良。

Aiming at the problem that the low matching accuracy of the current stereo matching algorithm cannot achieve the practical high precision level.This paper proposes a multi-feature stereo matching algorithm combining improved Census transform,color information and gradient measure,so as to realize high-precision binocular stereo matching.Firstly,in the initial cost matching phase,the improved Census transform,color and gradient measure are summed to obtain a reliable initial matching cost.In the aggregation phase,the efficient and fast minimum spanning tree aggregation is adopted to obtain the matching cost matrix.Finally,the initial disparity map is obtained according to the winner's strategy,and the disparity map is optimized by the left and right consistency detection method to obtain a high-precision disparity map.Experiments on the standard test charts provided on the Middlebury website show that the average mismatch rate of the disparity maps of the 15 test data sets obtained by the algorithm is 6.81%.The algorithm has excellent real-time responsiveness.