基于互信息的亚像素级立体视觉点匹配方法研究  

Sub-Pixel Point Matching Method of Stereo Vision Based on Mutual Information Theory

作　　者：孙少杰[1] 杨晓东[1] 任继昌[1] 

机构地区：[1]海军潜艇学院,山东青岛266042

出　　处：《电光与控制》2015年第4期23-26,31,共5页Electronics Optics & Control

基　　金：海军装备部军内科研项目

摘　　要：在立体视觉测量中,为获得更高精度,往往需要将视差计算精确到亚像素级。将互信息理论引入双目图像配准并结合多分辨率技术实现亚像素级点匹配。采用Bouguet立体校正算法对左右图像进行极线校正,利用Harris角点探测器检测目标并将获取角点作为待匹配点,采用最大互相关法进行搜索确定像素级匹配点。然后对以左右匹配点为中心的20×20邻域图像进行插值并分别放大10倍和100倍,采用互信息方法先对低分辨率图像进行配准,再在高分辨率图像上进一步细化求精,结合像素级匹配的整数视差可得最终亚像素级视差。实验结果表明,该方法能将视差精度提高到0.01像素。In order to improve the range-measuring accuracy in stereo vision,a sub-pixel parallax is needed. The Mutual Information（ MI） theory is combined with multi-resolution method to realize the goal of sub-pixel point matching. Firstly,Bouguet algorithm is used to rectify the left and right images making their epipolar line forward-paralled. Then Harris corner detector is brought to find a most characteristic corner as candidate matching point. After that,Most Cross Correlation matching rule is introduced to search the matching point. The 20 × 20 areas whose center is the left and right matching point are magnified by 10 and100 times respectively. The low-resolution image is registered with MI theory,followed by the seeking of higher precision in the high-resolution image. Finally,combined with the integer-grade parallax,we can get the sub-pixel parallax. The experimental result shows that the method used in this article can improve the precision to 0. 01 pixel level.

关 键 词：立体视觉 图像配准 互信息 多分辨率 亚像素 

分 类 号：V271.4[航空宇航科学与技术—飞行器设计]