In stereo matching tasks, the matching effect is often very poor when the texture of the region is weak or repeated. To solve this problem, an improved Graph Cut stereo matching algorithm based on Census transform is proposed. The Hamming distance of the corresponding pixels in the left and right images after Census transform is introduced as the similarity measure in the data term of the energy function. In this way, the dependence on the pixel value is reduced. The stereo matching experiments are implemented on the standard images of Middlebury stereo benchmark and the real scene images, and it demonstrates that our algorithm is robust and can obtain better performance in weak texture or repeated texture region.

在立体匹配任务中，当区域的纹理较弱或重复时，匹配效果往往很差。针对这一问题，提出了一种基于Census变换的改进Graph Cut立体匹配算法。在能量函数的数据项中引入了Census变换后左右图像中对应像素的汉明距离作为相似性度量。这样，减少了对像素值的依赖。在 Middlebury 立体基准的标准图像和真实场景图像上进行了立体匹配实验，表明我们的算法具有鲁棒性，在弱纹理或重复纹理区域可以获得更好的性能。