This Letter presents an improvement of disparity map refinement stage using adaptive least square plane fitting technique. This technique is proposed to increase the accuracy on the final stage of stereo matching algorithm. Fundamentally, the accuracy of matching process depends on the robustness of an algorithm on the plain colour region, depth discontinuity and repetitive pattern area. These regions are difficult to be matched and very challenging. Thus, this Letter proposes multiple point selections of disparities on a plane to adaptively group similar disparity values. Then, the distance of each disparity is calculated to ensure the values are accurately grouped. The distance refers to an assigned reference radius disparity location. Based on the experimental results using the KITTI and Middlebury benchmark images, the proposed method is capable of increasing the accuracy on the challenging regions and the quantitative measurement.

中文翻译：

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使用自适应最小二乘平面拟合技术改进视差图细化阶段

这封信提出了使用自适应最小二乘平面拟合技术对视差图细化阶段的改进。提出该技术是为了提高立体匹配算法最后阶段的准确性。从根本上说，匹配过程的准确性取决于算法对素色区域、深度不连续性和重复图案区域的鲁棒性。这些区域很难匹配并且非常具有挑战性。因此，这封信提出了平面上视差的多点选择，以自适应地对相似的视差值进行分组。然后，计算每个视差的距离以确保值被准确分组。距离是指分配的参考半径差异位置。基于使用 KITTI 和 Middlebury 基准图像的实验结果，