Fast stereo matching with predictive search range

Local stereo matching could deliver accurate disparity maps by the associated method, like adaptive support-weight, but suffers from the high computational complexity, O(NL), where N is pixel count in spatial domain, and L is search range in disparity domain. This paper proposes a fast algorithm that groups similar pixels into super-pixels for spatial reduction, and predicts their search range by simple matching for disparity reduction. The proposed algorithm could be directly applied to other local stereo matching, and reduce its computational complexity to only 8.2%-17.4% with slight 1.5%-3.2% of accuracy degradation.