Cross-scale cost aggregation integrating intrascale smoothness constraint with weighted least squares in stereo matching.

Cross-scale cost aggregation (CSCA) allows pixel-wise multiscale interaction in the aggregated cost computation. This kind of multiscale constraint strengthens the consistency of interscale cost volume and behaves well in a textureless region, compared with single-scale cost aggregation. However, the relationship between neighbors' cost is ignored. Based on the prior knowledge that costs should vary smoothly, except at object boundaries, the smoothness constraint on cost in a neighborhood system is integrated into the CSCA model with weighted least squares for reliable matching in this paper. Our improved algorithm not only has the advantage of CSCA in computational efficiency, but also performs better than CSCA, especially on the KITTI data sets. Experimental evidence demonstrates that the proposed algorithm outperforms CSCA in textureless and discontinuous regions. Quantitative evaluations demonstrate the effectiveness and efficiency of the proposed method for improving disparity estimation accuracy.