为了满足月球车视觉系统检测障碍物的时效性和可靠性需求, 提出了一种基于平面约束和自适应惩罚参数的半全局立体匹配算法。首先, 对极线校正后的两幅图像进行SIFT特征点提取与匹配, 同时提取边缘特征; 然后, 利用匹配的SIFT特征点拟合空间平面, 并根据平面估计左右图像所有像素点的视差搜索范围; 最后, 基于传统的半全局匹配算法, 采用自适应惩罚参数对左右图像进行立体匹配。实验结果表明: 所提出的算法有效地降低了计算复杂度, 其计算复杂度只有传统方法的19.9%, 对于视差不连续区域以及遮挡区域都能够获得正确的匹配结果。较传统半全局匹配方法无论在速度还是匹配精度上都得到明显提高, 为立体匹配的实际应用奠定了基础。

To meet the requirements of timeliness and reliability of the lunar rover system for obstacle detection, a semi-global stereo-matching algorithm based on the plane constraint and adaptive penalty coefficient was proposed. First, the Scale Invariant Feature Transform (SIFT) feature extraction and matching algorithm was used with two images of epipolar rectification from which edges are extracted. Second, the matched SIFT feature points were used to fit the plane, and the disparity search ranges of all pixels were estimated in the left and right images. Finally, based on the traditional semi-global matching algorithm, the adaptive penalty parameter strategy was applied to the stereo matching of the left and right images. Experimental results show that the algorithm can effectively reduce computational complexity to 19.9% that of the traditional methods. In addition, this method can obtain accurate matching results for the disparity discontinuous and occlusion regions. Compared with the traditional semi-global matching method, the processing speed and matching accuracy are clearly improved. This method can provide a foundation for further application.