鲁棒图像歧义性的立体匹配

采用独特性不相似测度的初始匹配和贪婪视差估计后处理相结合的方法，实现了基于局部信息的立体匹配. 首先，通过分析立体匹配本身的内在问题，构造匹配代价，得到初始视差. 然后采用新颖的视觉估计算法，包括不可靠视察检测、贪婪视差填充及多方向加权最小二乘拟合法，以消除宽遮挡等复歧义性. 实验结果表明，本算法结构简单，能降低歧义区域的误匹配，生成稠密、高精度的视差.

Robust Stereo Matching under Point Ambiguity

We propose a local stereo mathing algorithm, which relies on combination initial matching via distinctive dissimilarity measure with post-processing by greedy disparity estimation. Based on a dissimilarity measure derived from the stereo itself, the matching costs are first constructed to obtain initial disparities for both views. Then, in order to address complex ambiguity in large occluded regions, a novel disparity estimation procedure including unreliable disparity detection, greedy disparity filling and multi-directional weighted least-square-error fitting is presented to improve matching performance. Experimental results indicate that the proposed method can reduce false matching in ambiguous regions to generate a dense disparity accurately and efficiently.