立体匹配的关键问题是确定一个合适的匹配代价关系,颜色内相关作为像素点的固有特性，能够有效地反映出匹配像素点间的微小差异。对传统的自适应支撑权重 (ASW)方法进行改进，提出了一种基于颜色内相关和自适应支撑窗口的立体匹配算法，该方法结合了颜色相似性、欧式距离相似性和颜色内相关相似性来确定匹配窗口内像素点的权重大小。同时为了消除光照不同对图像匹配结果的影响，将匹配点先进行rank变换后再进行匹配代价关系计算。对计算出的初始视差图进行三步优化，剔除由图像遮挡、重复等引起的不同视差错误，从而得到最终的视差结果。通过在Matlab软件平台上对国际标准图像进行测试，实验结果表明该方法得到的视差结果的平均错误率低，且明显优于其他局部匹配方法，具有很强的稳健性和较低的误匹配率。

It is crucial to choose a suitable matching cost relationship for area-based stereo matching. Inter color correlation as the inherent characteristics of pixel, can effectively show the small matching differences between pixel. The traditional method of adaptive support weight is improved, and a new matching algorithm that combines the color similarity, Euclidean distance similarity and inter color correlation similarity is proposed to compute the corresponding support weight. Meanwhile, in order to solve the brightness difference between the stereo image pairs, matching pixel are transformed by rank and calculating the matching cost relationship. Various errors in the disparity results are effectively handled in a three-step refinement process. The experimental results based on Matlab show that its performance is the best among local matching methods, and its robustness is very strong, as well as low false match rate.