摘要： 在传统的全局立体匹配方法中,基于像素点的置信传播存在计算量大、单个像素点容易导致误差等缺点。为此,在图像分割处理方法的基础上,提出基于简单线性迭代聚类图像分割的循环置信度传播(LBP)立体匹配算法。运用LSC算法对图像进行分割,并利用一组平面模型进行建模,使每个分割区域至少对应一个视差平面标签。引入自适应匹配代价计算视差,获取可靠匹配像素点,通过最小二乘法平面拟合进行视差平面估计,并运用LBP算法优化视差平面标签。实验结果表明,与GC+occ、MultiCamGC等算法相比,该算法具有较高的匹配精度,能够处理低纹理区域和遮挡区域。

关键词: 立体匹配, 简单线性迭代聚类, 自适应匹配代价, 平面拟合, 循环置信度传播

Abstract: In the traditional global stereo matching methods,pixel-based belief propagation has a large amount of computation and a single pixel point can easily cause errors.Therefore,on the basis of the image segmentation processing methods,a Loopy Belief Propagation(LBP) stereo matching algorithm based on Simple Linear Iterative Clustering(SLIC) image segmentation is proposed.The image is segmented using the LSC algorithm and modeled using a set of plane models so that each segmentation region corresponds to at least one parallax plane label.The self-adapting matching cost calculation parallax is introduced to obtain reliable matching pixels,and the parallax plane estimation is performed by least squares plane fitting,and the LBP algorithm is used to optimize the parallax plane label.Experimental results show that compared with GC+occ,MultiGC and other algorithms,the algorithm has high matching accuracy and can handle low texture areas reas.

Key words: stereo matching, Simple Linear Iterative Clustering(SLIC), self-adapting matching cost, plane fitting, Loopy Belief Propagation(LBP)

中图分类号: 

• TP391