A color-based approach for disparity refinement

We present a new disparity refinement algorithm that utilize color information of the reference image to generate sharp disparity maps. While existing methods use iterative approaches or require multiple disparity maps, the proposed algorithm uses a single pass approach to reduce errors at depth discontinuities. The experimental results are evaluated on the Middlebury benchmark dataset; show the effectiveness of the proposed algorithm.