To solve the problem of low matching accuracy in textureless regions, a local stereo matching method is proposed based on improved cost computation and adaptive shape guided filter. First, an efficient cost function combining enhanced image gradient and enhanced gradient-based Census transform is introduced for cost computation. Then, an adaptive shape cross-based window is constructed for each pixel, and guided filter aggregation is implemented based on this adaptive window. The final disparity map is obtained after disparity computation and multi-step disparity refinement. The experimental results demonstrate that the average matching error rate of the proposed algorithm is 4.80% for stardard image paris on Middlebury benchmark. Compared with traditional guided filter-based method, the proposed method has better matching results in textureless regions.