目的 基于区域的局部匹配算法是一种简单高效的立体匹配方法。针对局部算法中窗口的抉择问题,提出了基于垂直交叉双向搜索的自适应窗口匹配算法。方法 该算法考虑到局部区域内灰度值与视差值的相关性,通过垂直交叉双向搜索策略自适应地调节窗口的形状和大小,并获得相应掩码窗口;再利用积分图像计算掩码窗口的匹配代价,获取视差图;最后采用米字投票和双边滤波器两个步骤对视差图进行修复。结果 针对不同图像采用提出的自适应窗口算法,得到了适用于各种图像结构的匹配窗口,相较于原始垂直交叉算法的匹配精度提高了约30%(Teddy),同时两步骤视差后处理较好地保持了图像边缘。结论 实验结果表明,该算法改善了规则窗口产生的视差边缘扩充问题,在提高视差精度的同时提高了算法鲁棒性。

Objective Region-based local match methods are the simplest and most effective stereo matching algorithms. Considering the problem of the window chosen in the local methods, we propose a cross-based bidirectional adaptive window-matching algorithm. Method In this algorithm, we construct the support window adaptively by cross-based bidirectional search, which is based on the correlation of intensity and disparity in the image patches, and obtain a mask window. The integral images are adopted to calculate the matching costs in the mask window. Thus, disparity map is obtained. Two steps are implemented: Union Jack-shaped voting and bilateral filtering algorithm as a post-processing step. Result The proposal is adopted on different stereo images, and adaptive match windows are obtained for the image structures. The matching accuracy is increased by 30% for Teddy compared with the original cross-based method. The two-step disparity post-processing keeps the edges of the images well. Conclusion Experimental results show that the proposed algorithm alleviates the depth edge expansion problem introduced by regular window as well as improves the robustness and depth accuracy of the algorithm.