摘要
为了快速消除双目立体匹配的歧义性,提出一种基于局部信息和分割、快速高效的两步立体匹配算法.首先分割彩色立体图像对,并基于改进的Geman-McClure函数得到初始匹配成本;在水平、垂直双方向上采用分割自适应权重方法,消除匹配特征的相似歧义,计算鲁棒匹配代价,择优选取初始视差.为了最优地分配遮挡等歧义区域,采用贪婪策略估计视差,包括不可靠视差检测、基于分割窄遮挡处理、基于极线最小二乘填充及基于映射的视差组合.实验结果表明,该算法结构简单、计算快速高效,能有效地消除匹配歧义,得到分段平滑、精度高的稠密视差图;可在临床医学疾病诊断应用中自动地为计算机辅助诊断系统提供可靠深度信息感知.
A segmentation-based two-step stereo matching is proposed in a fast and local perspective to resolve the ambiguity of binocular stereo problem in this paper.Color segmentation is firstly conducted on both stereo pairs,then robust matching costs are constructed with modified Geman-McClure function and segmentation-based variable support two-pass aggregation only in the horizontal and vertical directions which eliminate ambiguity in feature matching,and then initial disparity map is obtained from them.To assign optimal disparity to ambiguous regions（such as occlusion etc.）,greedy disparity estimation consists sequentially of four parts： unreliable disparity detection,segmentation-based narrow occlusion handling,epipolar-line-based least square filling and warping-based disparity combination.The experimental results indicate that this technique can eliminate matching ambiguity and obtain piecewise smooth,accurate and dense disparity map effectively.This algorithm is concise,fast and efficient so that it could provide automatic and reliable depth perception for computer aided diagnosis system in clinical medical application diagnosing diseases.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2010年第1期100-107,共8页
Journal of Computer-Aided Design & Computer Graphics
关键词
机器视觉
双目立体匹配
基于分割的可变权值
最小二乘拟合
临床医学诊断
Machine vision binocular stereo matching segmentation-based variable support weight least square fitting clinical medical diagnosis
