关键词: 立体匹配, 尺度, 支持窗口, 盒滤波, 引导滤波, 加权中值滤波

Abstract: A novel cross-scale cost aggregation framework with dynamic support windows is introduced to address the fundamental challenge of local stereo matching algorithms, accuracy and computational complexity dilemma. The matching cost volume is aggregated at each scale separately with box filtering whose support windows are dynamic inter-scales. An inter-scale regularizer is introduced into optimization and solving this new cross-scale cost aggregation problem. Weighted median filtering is used for disparity refinement with guided filter weight. Experimental results show that the proposed method achieves theoretically strong results effectively and efficiently, with the two main steps’ complexity independent of the filtering kernel size. The algorithm achieves good performance in terms of both speed and accuracy.

Key words: stereo matching, scale, support window, box filter, guided filter, weighted median filter