The parallax pattern obtained from the ELAS (efficient large-scale stereo matching) algorithm contains obvious fringes and void regions. To address this problem, a stereo matching algorithm that combines matching window characteristics with differentials is proposed in this paper. By enhancing the description of the feature information of points, the similarity measure of the points to be matched is provided with a higher degree of discrimination. First, according to the classical adaptive algorithm of color images, a window descriptor adapted to a gray image was proposed spatially. Next, according to the characteristics of an image signal, a less smooth differential operator was selected at the pixel level. Then the proposed matching window was combined with a differential operator to obtain a description ability of feature information stronger than either of the two. Finally, objective evaluation of standard benchmarks and subjective evaluation of self-collected images show that the proposed algorithm is more robust and has higher matching accuracy, and it obviously improves phenomena related to stripes and void regions in the disparity map.