Binocular stereo vision processes estimate 3D surfaces using a pair of images taken from different points of view. For that, 3D surface characteristics are estimated by matching 2D image features corresponding to the projections of same 3D points. The most classic feature-based methods used cross correlation with a fixed window-size, but this technique presents a major drawback : the computation of depth is generally false close to surface discontinuities. In this paper, we present our current work on aerial stereo images of urban areas. A correlation-based algorthm with an adaptive window-size constrained by an edge map extracted from the images is presented. The algorithm follows 4 steps : first window sizes for each pixel are computed ; then a disparity map is created ; third, map completion is performed and finally a final dense disparity map with subpixel precision is produced. Experimental results on real aerial images are presented.