基于跨尺度引导图像滤波的稠密立体匹配  

Dense Stereo Matching Based on Cross-Scale Guided Image Filtering

作　　者：刘杰[1] 张建勋[1] 代煜[1] 苏赫 Liu Jie;Zhang Jianxun;Dai Yu;Su He(Institute of Robotics ＆Automatic Information System, Nankai University Tianjin 300071, China)

机构地区：[1]南开大学机器人与信息自动化研究所,天津300071

出　　处：《光学学报》2018年第1期224-230,共7页Acta Optica Sinica

基　　金：国家自然科学基金(51375494;61403212);国家重点研发计划(2017YFC0110402)

摘　　要：针对现有局部立体匹配算法在弱纹理表面、深度不连续处等特定区域匹配精度低、实时性难以满足要求等问题,提出了一种基于跨尺度引导图像滤波的稠密立体匹配算法。利用图像分割技术对立体图像进行预分割,得到分割区域内像素的聚合半径;以此半径为指导,在立体图代价空间中以3种不同尺寸的核进行滤波,引入正则化项确保聚合代价的一致性,以得到更有效的聚合代价;运用简单高效的贪心策略获取初步视差。基于Middlebury测试平台的实验结果表明所提算法兼具实时性和高效性。To solve problems of the difficulty to meet the real-time requirements and the low matching accuracy of existing local stereo matching algorithms at some special regions,such as weak textured surfaces and the discontinuity boundary of depth,a dense stereo matching algorithm based on cross-scale guided image filtering is proposed.An image segmentation technology is used to realize pre-segmentation of stereo images and the aggregation radius of pixels in the segmented region is obtained.This radius is used as a guide,and kernels with three different sizes are used to carry out filtering in the cost space of stereo image.The regularization term is introduced to ensure the consistency of the aggregated cost,so as to obtain a more efficient aggregate cost.A simple and efficient winner-take-all strategy is used to obtain the initial disparity.The experimental results based on Middlebury test bench show that the proposed algorithm has both real time capability and high efficiency.

关 键 词：机器视觉 信号处理 引导滤波 立体匹配 正则化 跨尺度 聚合代价 

分 类 号：TN911.73[电子电信—通信与信息系统]