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 performed iteratively to update the low confident disparities with the information provided by extra image bit-planes. Since the disparity computation is carried out on a need-to-know basis, the proposed technique is suitable for remote processing of the images acquired by a mobile camera. Our method provides a hierarchical matching framework and can be combined with the existing stereo matching algorithms. Experiments on Middlebury datasets show that our technique gives good results compared to the conventional full bit-rate matching.
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Lin, HY., Lin, PZ. (2013). Hierarchical Stereo Matching Based on Image Bit-Plane Slicing. In: Park, JI., Kim, J. (eds) Computer Vision - ACCV 2012 Workshops. ACCV 2012. Lecture Notes in Computer Science, vol 7729. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37484-5_48
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DOI: https://doi.org/10.1007/978-3-642-37484-5_48
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