In order to improve the accuracy of local stereo matching, a stereo matching algorithm based on improved Census cost and optimized guided filtering is proposed. Aiming at the problem that the traditional Census cost calculation is not accurate in the cost calculation of disparity discontinuous region, the neighborhood pixel validity label is carried out in the Census transformation process, and the influence of invalid pixels on the overall cost is reduced by calculating different generation values for different validity points. In the stage of guided filtering cost aggregation, two sizes of windows are used to calculate the linear coefficients, and then different linear coefficients are selected according to the results of image region division, which solves the problem of inadaptability of local region cost aggregation caused by fixed window size. Finally, the final disparity map is obtained by disparity calculation and disparity optimization. Experiments were carried out on the Middlebury v3 stereo matching evaluation platform. The results show that the average mismatch rates of the proposed algorithm in the non-occluded area and in all areas are 18.17% and 23.81%, respectively, which are better than many existing algorithms.