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Hierarchical stereo matching with image bit-plane slicing

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Abstract

We propose a new stereo matching framework based on image bit-plane slicing. A pair of image sequences with various intensity quantization levels constructed by taking different bit-rate of the images is used for hierarchical stereo matching. The basic idea is to use the low bit-rate image pairs to compute rough disparity maps. The hierarchical matching strategy is then carried out iteratively to update the low confident disparities with the information provided by extra image bit-planes. It is shown that, depending on the stereo matching algorithms, even the image pairs with low intensity quantization are able to produce fairly good disparity results. Consequently, variate bit-rate matching is performed only regionally in the images for each iteration, and the average image bit-rate for disparity computation is reduced. Our method provides a hierarchical matching framework and can be combined with the existing stereo matching algorithms. Experiments on Middlebury datasets show that the proposed technique gives good results compared to the conventional full bit-rate matching.

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Notes

  1. For example, most digital cameras, especially for the mid- to high-end models, have 14 or 12 bits per pixel in their internal or RAW image formats.

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Acknowledgments

The support of this work in part by the National Science Council of Taiwan, R.O.C, under Grant NSC-99-2221-E-194-005-MY3 is gratefully acknowledged.

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Authors and Affiliations

  1. Department of Electrical Engineering and Advanced Institute of Manufacturing with High-tech Innovation, National Chung Cheng University, 168 University Road, Min-Hsiung, Chiayi, 621, Taiwan

    Huei-Yung Lin & Pin-Zhi Lin

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  1. Huei-Yung Lin
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  2. Pin-Zhi Lin
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Correspondence to Huei-Yung Lin.

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Lin, HY., Lin, PZ. Hierarchical stereo matching with image bit-plane slicing. Machine Vision and Applications 24, 883–898 (2013). https://doi.org/10.1007/s00138-012-0452-2

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