Abstract

Gradient similarity is a simple, yet powerful, data descriptor which shows robustness in stereo matching. In this paper, a RGB vector space is defined for stereo matching. Based on the adaptive support-weight approach, a matching algorithm, which uses the pixel gradient similarity, color similarity, and proximity in RGB vector space to compute the corresponding support-weights and dissimilarity measurements, is proposed. The experimental results are evaluated on the Middlebury stereo benchmark, showing that our algorithm outperforms other stereo matching algorithms and the algorithm with gradient similarity can achieve better results in stereo matching.

© 2012 Optical Society of America

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