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.