基于自适应极线距离变换的立体匹配  

Adaptive Epipolar Distance Transform-Based Stereo Matching

作　　者：符立梅[1] 彭国华[1] 

机构地区：[1]西北工业大学理学院,西安710129

出　　处：《计算机辅助设计与图形学学报》2015年第3期394-399,共6页Journal of Computer-Aided Design & Computer Graphics

基　　金：国家自然科学基金(61070233)

摘　　要：针对极线距离变换对噪声的敏感性及其在不连续区域匹配的不确定性,提出一种基于自适应极线距离变换的立体匹配算法.自适应极线距离变换利用图像结构特征,提出迭代目标尺度算法与区域不连续图来自适应选择极线距离变换参数,将图像的强度信息转化为沿着极线局部分割区域的相对位置信息,在区分低纹理区域像素点的同时保持了图像边缘信息;采用局部极小窗口均值计算分割线长度,有效地提高了低纹理区域对噪声的鲁棒性.对多幅真实图像的实验结果表明,自适应极线距离变换对低纹理区域以及不连续区域是有效的,且采用变换后图像计算视差的立体匹配算法,有效地降低了图像边缘点和噪声点等不连续区域的误匹配率,提高了图像匹配精度.Considering the epipolar distance transform-based stereo matching is sensitive to noise and ambiguous in discontinuous regions, an adaptive transform-based stereo matching algorithm is proposed. By employing image structure features, an iterative object＇s scale algorithm and a block discontinuous map are proposed to choose the parameters adaptively. This transform converts image intensity values to a relative location inside a planar segment along the epipolar line, so that the pixels in the low-texture regions become distinguishable, and the edges are preserved. Besides, the mean value in the local window is adopted to calculate the length of segmentation line, improving the robustness to noise of pixels in low texture area. Experimental results on several real images demonstrate the effectiveness of the proposed transform in low-texture regions and discontinuities regions. When the stereo matching algorithms use the proposed transformed images to obtain disparity maps, the matching accuracy is improved and the matching errors of discontinuous regions, such as edges and noises, are reduced.

关 键 词：不连续区域 立体匹配 自适应极线距离变换 迭代目标尺度算法 区域不连续图 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]