Modified adaptive support weight for stereo matching

Abstract

Stereo matching using local algorithms are incredibly popular in the last years. The adaptive support weight algorithms can give high accuracy results such as global methods. This paper proposes a support aggregation approach for stereo matching that computes support weight in sparse support window mask. The improvement from the previous work is that the new support weight can reduce the computation time. At the end of the research, the result shows that the computation time decreases to approximately half to a quarter of the earlier work time without significant difference of bad pixel percentage and help to reach the optimum correspondence. It means sparse support weight affects the computation time that is needed in stereo matching and optimizes the disparity. This support weight isused to accomplish the stereo matching evaluation using this method. This approach is more reliable than the previous approach in the real implementation.