Abstract: A kind of area matching method that combined weights matrix with similarity coefficient matrix was proposed in this article. The article was organized as follows: first of all, the method got the weights matrix by using color similarity and distance proximity, and the value of the matrix was corrected with an edge matrix for improving correction of the edge pixels. Then a similarity coefficient matrix was adaptively obtained according to each point pairs sum of absolute difference in matching window between left image and right image. Finally, the method was investigated by matching four stereo images (Tsukuba, Venus, Teddy, and Cones) with ground truth provided in Middlebury stereo database and the rate of overall accuracy reaches 91.82%,96.19%,76.6%,86.9%，respectively.

Key words: stereo matching, weights matrix, edge pixel, similarity coefficient, parallax image

摘要： 提出了一种结合权值矩阵和相似性系数矩阵构造的区域匹配方法。该方法首先运用色彩相似性和距离临近性对窗内的每一点相对于待匹配点的自适应权值进行分配，得到一个权值矩阵，为了提高在视差不连续区域的匹配精度，使用了边界点矩阵来降低相对应点的权值。然后在RGB色彩空间中根据待匹配点和对应点的匹配窗内的每一点的颜色绝对差值和来自适应分配相似性系数矩阵。最后利用上述方法对Middlebury网站上提供的四幅立体图像对Tsukuba、Venus、Teddy和Cones进行了实验，总体正确率分别达到了91.82%、96.19%、76.6%和86.9%。

关键词: 立体匹配, 权值矩阵, 边界点, 相似性系数, 视差图