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International Conference on Intelligent Computing

ICIC 2016: Intelligent Computing Theories and Application pp 61–73Cite as

Stereo Matching with Improved Radiometric Invariant Matching Cost and Disparity Refinement

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9771))

Abstract

Accurate and real-time stereo correspondence is a pressing need for many computer vision applications. In this paper, an improved radiometric invariant matching cost algorithm is proposed. It effectively combines modified census transform with relative gradients measures. Although it is very simple, comparison results on Middlebury stereo testbed demonstrate that it has much lower error rates than many existing algorithms and is very close to the ANCC algorithm which represents the current state of the art under extreme luminance condition but outperforms the ANCC algorithm greatly when there are small radiometric distortions. In addition, we also develop a disparity refinement method with computational complexity invariant to the disparity range. Experimental results on Middlebury datasets show those artifacts near object boundaries are reduced using the proposed disparity refinement method.

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Notes

  1. 1.

    For gray input image, \( W_{p,q} (I) = \exp ( - |I(p) - I(q)|/\delta ) \).

  2. 2.

    Note that since this paper is not to evaluate cost aggregation algorithm, the Middlebury 2014 datasets which contain several new features are not used for evaluation.

  3. 3.

    For implementing BT, we used the code provided in [11].

  4. 4.

    For the runtime of ANCC, we direct use the results reported in [21].

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Acknowledgments

This work was supported by a grant from National Natural Science Foundation of China (NSFC, No. 61504032).

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Authors and Affiliations

  1. Microelectronics Center, Harbin Institute of Technology, Harbin, 150000, China

    Jinjin Shi, Fangfa Fu, Yao Wang, Weizhe Xu & Jinxiang Wang

Authors
  1. Jinjin Shi
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  2. Fangfa Fu
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  3. Yao Wang
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  4. Weizhe Xu
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  5. Jinxiang Wang
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Corresponding author

Correspondence to Jinxiang Wang .

Editor information

Editors and Affiliations

  1. Tongji University , Shanghai, China

    De-Shuang Huang

  2. Polytechnic of Bari , Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong , North Wollongong, New South Wales, Australia

    Prashan Premaratne

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Shi, J., Fu, F., Wang, Y., Xu, W., Wang, J. (2016). Stereo Matching with Improved Radiometric Invariant Matching Cost and Disparity Refinement. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9771. Springer, Cham. https://doi.org/10.1007/978-3-319-42291-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-42291-6_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42290-9

  • Online ISBN: 978-3-319-42291-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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