In order to improve the stereo matching accuracy, a fusion stereo matching algorithm of adaptive SAD with super-pixel segmentation constraints and Census algorithm is proposed. To address the errors introduced by the indiscriminate use of the grayscale values of the pixel points within the window in the stereo matching process of SAD, First the super-pixel segmentation method of Simple Linear Iterative Clustering (SLIC) is used to process the map to be matched, and the segmentation results are combined with the distance between the neighboring pixel points and the center pixel point within the window to assign appropriate weights to the grayscale values of the pixel points within the window in the SAD stereo matching process; Subsequently, the Census stereo matching process is performed, and the matching results of the two algorithms are adaptively fused; Finally, post-processing processes such as left-right consistency detection and occlusion point filling are performed on the Initial parallax map. The experiments show that the algorithm is significantly better than the traditional algorithm in terms of matching effect, can be well adapted to detail-rich images and has better adaptability to groups with vertical shifts, and is robust to image contrast and illumination changes.