基于自适应匹配窗及多特征融合的立体匹配*

针对局部立体匹配方法中存在的匹配窗口大小选择困难、边缘处视差模糊及弱纹理区域、斜面或曲面匹配精度较低等问题，提出基于CIELAB空间下色度分割的自适应窗选取及多特征融合的局部立体匹配算法.首先，在CIELAB空间上对立体图像对进行色度分割，依据同质区域的分布获取初始匹配支持域，同时估计遮挡区域，更新匹配支持域.然后，基于更新后的匹配支持域，采用自适应权值的线性加权多特征融合匹配方法得到初始视差图.最后，利用左右视差一致性检测方法进行误匹配检验，利用基于分割的均值滤波器进行视差优化及细化，得到稠密匹配视差结果.实验表明文中算法有效，匹配精度较高，尤其在弱纹理区域及斜面等情况下匹配效果较好.

Stereo Matching Based on Adaptive Matching Windows and Multi-feature Fusion

Aiming at the problems of local stereo matching methods, such as difficulties in matching window selection, vague disparity of edges and low accuracy in weak texture regions and slope surface regions, an efficient stereo matching algorithm with adaptive support window based on segmentation in CIELAB color space and multiple features fusion is proposed in this paper. Firstly, the stereo images are segmented in CIELAB color space, the initial support window is calculated according to the homogeneous regions, and the initial support window is updated by estimating the occlusion region. And then the initial disparity map in the updated support region is achieved by the linear weighted multi-feature fusion matching method with adaptive weights. Finally, the mismatch is checked by consistency of right disparity and left disparity, and then the ultimate dense disparity map is obtained through disparity optimization by mean filtering and disparity refinement. Experimental results show that the proposed algorithm is effective with high matching precision, especially for weak texture and slope surface regions.