In this study, we propose a local stereo matching algorithm based on guidance images and an adaptive support region. First,the guidance images can be obtained by preprocessing the rectified input images. During the matching cost calculation stage, we propose a gradient calculation method, which combines the gradient information of the guidance and input images to calculate the gradients along the x and y directions, respectively, and subsequently integrates the absolute difference (AD) and the Census transform to develop a matching cost calculation function. Further, we use a guided filter based on the adaptive support region during the cost aggregation stage. During the disparity refinement stage, a multi-step refinement method is proposed based on the adaptive support region and then the final disparity map is obtained. The experimental results prove that after disparity refinement, the average error (Avgerr) and root-mean-square error (RMSE) are reduced by 43.7% and 38% respectively for all the regions and by 33.7% and 30.9% for the non-occluded regions. The proposed algorithm exhibits improved robustness and can be used to obtain high precision disparity results.