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Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 51, Iss. 16 — Jun. 1, 2012
  • pp: 3538–3545

Stereo matching based on adaptive support-weight approach in RGB vector space

Yingnan Geng, Yan Zhao, and Hexin Chen  »View Author Affiliations

Applied Optics, Vol. 51, Issue 16, pp. 3538-3545 (2012)

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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

OCIS Codes
(330.1400) Vision, color, and visual optics : Vision - binocular and stereopsis
(330.1720) Vision, color, and visual optics : Color vision

ToC Category:
Vision, Color, and Visual Optics

Original Manuscript: January 5, 2012
Revised Manuscript: March 23, 2012
Manuscript Accepted: March 23, 2012
Published: May 31, 2012

Virtual Issues
Vol. 7, Iss. 8 Virtual Journal for Biomedical Optics

Yingnan Geng, Yan Zhao, and Hexin Chen, "Stereo matching based on adaptive support-weight approach in RGB vector space," Appl. Opt. 51, 3538-3545 (2012)

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