针对ELAS(Efficient Large-Scale Stereo Matching)算法视差图条纹明显且具有空洞区域的问题,提出一种匹配窗口特性与微分特性相结合的局部立体匹配算法,增强描述子对点特征信息的描述能力,为待匹配点提供更有区分度的相似性度量。先根据彩色图像的经典自适应算法,从空间上提出适应于灰度图像的窗口描述子,依据图像信号的特点,从像素层面上选择平滑性更小的微分算子。再将匹配窗口与微分算子相结合,获得比只使用两者之一更强的特性信息描述能力。最后进行标准数据集的客观检验与自采集图像的主观评价,结果表明该算法具有较强的鲁棒性和更高的匹配精度,明显改善了原匹配策略视差图中出现条纹及空洞的现象。

The parallax pattern obtained from the ELAS (efficient large-scale stereo matching) algorithm contains obvious fringes and void regions. To address this problem, a stereo matching algorithm that combines matching window characteristics with differentials is proposed in this paper. By enhancing the description of the feature information of points, the similarity measure of the points to be matched is provided with a higher degree of discrimination. First, according to the classical adaptive algorithm of color images, a window descriptor adapted to a gray image was proposed spatially. Next, according to the characteristics of an image signal, a less smooth differential operator was selected at the pixel level. Then the proposed matching window was combined with a differential operator to obtain a description ability of feature information stronger than either of the two. Finally, objective evaluation of standard benchmarks and subjective evaluation of self-collected images show that the proposed algorithm is more robust and has higher matching accuracy, and it obviously improves phenomena related to stripes and void regions in the disparity map.