Global method based on Tao stereo matching framework

Traditional stereo matching based on global optimization is of computational complex which is poor to get accuracy matching result for the pixels in occlusion and depth discontinuity region. An efficient method of stereo matching was proposed, which was based on Tao stereo matching framework. Firstly, the initial matching disparity was obtained by the enhanced local method. Then occlusion and mismatched pixels were applied from reliable pixels using the robust method and named unreliable pixels, then reliable pixels and presupposition of disparity plane were used to refine the unreliable disparity. Finally, in order to improve the disparity accuracy in low texture region, an enhanced belief propagation method was used to optimize the refined initial disparity, which had adaptive convergence threshold. Experimental results demonstrate that our method can reduce the error matching rate effectively, improve the matching accuracy in occlusion and depth discontinuity region, reduce the computational complexity as well as improve matching speed.