Adaptive support weights (ASW) are one of the best methods for matching costs in local stereo matching algorithms. In the literature, the most common method is guided filter for calculating the support weight. Guided filter-based methods generally apply the right-left consistency check during the disparity refinement process. However, this process requires the two difference maps which are obtained by taking the reference of the right image and the left image. In this case, since two difference maps need to be obtained, the processing load is almost doubled. With the proposed algorithm, the difference map for the left image is obtained with the winner-take-all (WTA) method after the costs are calculated with the help of the guided filter. Later on, this difference map has been corrected with the help of the cross-based window approach, by this, both the performance was improved and the processing costs were reduced, this resulted in a nearly twofold reducement in terms of the processing time. The results obtained were tested in the Middlebury dataset.