Abstract: Regional stereo matching algorithm is sensitive to illumination change. Disparity map has the problems that target and the weak texture region mismatch, boundary is not smooth, and so on. In order to solve these problems, an improved quick stereo matching algorithm by using visual saliency characteristics was proposed. Saliency detection was used to locate the main target area in the image. Then feature matching was completed by combining image Sobel edge characteristics and phase features to get the rough disparity map. Finally, by detecting visual saliency in the disparity map, abrupt noise in weak texture image area was eliminated. Compared to the traditional algorithms such as Sum of Absolute Differences (SAD), Sum of Squared Differences (SSD), Normalized Cross Correlation (NCC), the proposed algorithm is not sensitive to light changing, and it can get better disparity map and higher matching rate, which is conducive to real-time applications.

Key words: stereo matching, saliency, edge, phase angle, parallax optimization

摘要： 针对区域立体匹配算法对光照变化敏感,视差图存在目标和弱纹理区域的错配、边界不平滑等问题,提出一种利用视觉显著性特征改进的快速区域立体匹配算法。该算法先利用显著性检测定位图像主要目标区域;再结合索贝尔(Sobel)边缘特征和相角特征完成特征匹配、得到粗视差图;最后通过检测粗视差图中的视觉显著性,消除图像弱纹理区域的突兀噪声。相比绝对误差累计(SAD)、平方误差累计(SSD)和归一化灰度互相关(NCC)算法,所提算法对光照变化不敏感,得到的视差图完整,匹配率高,有利于实时系统应用。

关键词: 立体匹配, 显著性, 边缘, 相角, 视差优化