一种基于双重分割的立体匹配算法

A Dual Segmentation Based Stereo Matching Algorithm

立体匹配通过计算同一场景不同视点下图像的匹配像素的视差,恢复场景的深度信息.文中对传统的基于分割的立体匹配算法进行改进,提出了一种基于双重分割的立体匹配算法.首先对参考图像进行颜色欠分割,使每个区域包含足够的信息进行平面拟合;然后对初始匹配视差图进行分割,检测颜色分割中的欠分割区域并进行再分割,进而对再分割后的区域进行平面拟合;最后利用合作算法对不可信区域优化,以提高匹配算法的运行效率.Middlebury标准图像测试集上的实验结果表明,相对于传统分割算法,该算法时间开销更少、匹配精度更高.

Stereo matching is used to recover the depth of scene through computing disparity between matching pixels in the same scene under different viewpoints. A dual segmentation based stereo matching algorithm is presented by improving the traditional approaches. Firstly, it is to under- segment the reference image so that each region in the image contains sufficient cues for plane fitting. Secondly, it is to segment the initial disparity map for detecting and re-segmenting those under- segmented regions in reference image, and the processed results are plane fitted. Finally, to minimize processing time, only invalid regions are iteratively optimized by an inter-regional cooperative procedure. The experimental results on Middlebury test set show that our proposed algorithm achieves higher matching accuracy with less time than other well-established segmentation algorithms.