基于改进Census变换与多特征融合的立体匹配算法

Stereo Matching Algorithm Based on Improved Census Transform and Multi-Feature Fusion

立体匹配是三维重建技术中的关键步骤,针对局部立体匹配算法在弱纹理区域、深度不连续区域匹配效果差,且容易受到噪声干扰的问题,提出了一种基于多特征融合的局部立体匹配算法。对传统的Census变换进行改进,使其对噪声具有更强的鲁棒性,并将其与颜色特征、梯度特征相融合进行代价计算;采用多尺度下的引导滤波算法进行代价聚合,并通过视差计算与优化得到视差图。在Middlebury数据集上的实验结果表明,所提算法抗噪能力强,且与当前较为优秀的局部立体匹配算法相比,匹配精度有了进一步提升。

In the threedimensional reconstruction technology,stereo matching is a key step.Aiming at the problem that local stereomatching algorithms have poor matching effects in areas with weak texture and discontinuous depth and are easily disturbed by noise,a local stereomatching algorithm based on multifeature fusion is proposed.The traditional Census transform is improved to make it more robust to noise and is fused with color features and gradient features for cost calculation;the multiscale guided filtering algorithm is used for cost aggregation,and the disparity map is obtained through disparity calculation and optimization.The experimental results on the Middlebury dataset show that the proposed algorithm has strong antinoise ability,and the matching accuracy is further improved when compared with the current excellent local stereomatching algorithms.