曹晓倩, 马彩文. 一种光照度不一致鲁棒立体匹配算法[J]. 机器人, 2014, 36(5): 634-640. DOI: 10.13973/j.cnki.robot.2014.0634
引用本文: 曹晓倩, 马彩文. 一种光照度不一致鲁棒立体匹配算法[J]. 机器人, 2014, 36(5): 634-640. DOI: 10.13973/j.cnki.robot.2014.0634
CAO Xiaoqian, MA Caiwen. A Radiometric Varying Robust Stereo Matching Algorithm[J]. ROBOT, 2014, 36(5): 634-640. DOI: 10.13973/j.cnki.robot.2014.0634
Citation: CAO Xiaoqian, MA Caiwen. A Radiometric Varying Robust Stereo Matching Algorithm[J]. ROBOT, 2014, 36(5): 634-640. DOI: 10.13973/j.cnki.robot.2014.0634

一种光照度不一致鲁棒立体匹配算法

A Radiometric Varying Robust Stereo Matching Algorithm

  • 摘要: 为了提高光照度不一致立体图像对的匹配率,提出一种基于对数颜色空间下改进极线距离变换的立体匹配算法.在对数颜色空间下,首先根据初始视差图计算立体图像对的灰度比;然后,采用与灰度比成比例的灰度误差系数,分别对左右图像进行极线距离变换;最后利用置信度传播算法计算视差图.理论上,本文算法的匹配结果不会受光源位置、光源谱分布、光照强度以及摄像机参数设置等光照度不一致因素的影响.实验表明:本文算法的匹配率相对于原始极线距离变换算法最多可提高60%;而应用于弱纹理图像对时,相对于当前先进的自适应归一化算法,匹配率最多可提高78%.

     

    Abstract: In order to improve the matching rate of radiometric varying stereo images, a novel stereo matching algorithm based on the improved epipolar distance transformation in log-chromaticity space is proposed. In log-chromaticity space, the intensity proportion of stereo image pairs is computed firstly according to raw disparity map; secondly, epipolar distance transformation is performed on left and right images respectively using proportional intensity deviation parameters; at last, the final disparity map is acquired by the belief propagation method. Theoretically, the matching rate of the proposed algorithm is independent of radiometric varying situations including differences in light source's position, spectrum, intensity and the parameters setting of cameras. Experimental results indicate that the matching rate of the proposed algorithm is improved at most 60% comparing with the original epipolar distance transformation algorithm and at most 78% comparing with the state of art algorithms such as ANCC (adaptive normalized cross correlation) when applied to textureless image pairs.

     

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