A coarse to fine approach for fast stereo matching is presented. In this approach, a dynamic programming (DP) based algorithm at the top of the pyramid is applied to obtain an initial coarse dense disparity map of high quality and to reduce computational cost. In each finer layer, a new dense disparity map is inherited from the coarser layer by interpolation. The new dense disparity map will be updated only in selected areas, instead of the whole map, according to the local matching cost and the depth difference among neighbouring areas. In this way, the proposed approach is able to obtain a smooth dense disparity map and to preserve discontinuity as well. The approach is evaluated using rectified stereo images and good results are achieved in terms of quality and running speed
