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    Quantitative error analysis of bilateral filtering

    Access Status
    Fulltext not available
    Authors
    An, Senjian
    Boussaid, F.
    Bennamoun, M.
    Sohel, F.
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    An, S. and Boussaid, F. and Bennamoun, M. and Sohel, F. 2015. Quantitative error analysis of bilateral filtering. IEEE Signal Processing Letters. 22 (2): pp. 202-206.
    Source Title
    IEEE Signal Processing Letters
    DOI
    10.1109/LSP.2014.2353694
    ISSN
    1070-9908
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    URI
    http://hdl.handle.net/20.500.11937/69751
    Collection
    • Curtin Research Publications
    Abstract

    One of the fastest acceleration techniques for bilateral image filtering is the real time $O(1)$ quantization method proposed by Yang 2009, which first computes some Principal Bilateral Filtered Image Components (PBFICs) and then applies linear interpolation to estimate the filtered output images. There is a trade-off between accuracy and efficiency in selecting the number of PBFICs: the more PBFICs are used, the higher the accuracy, and the higher the computational cost. A question arises: how many PBFICs are required to achieve a certain level of accuracy? In this letter, we address this question by investigating the properties of bilateral filtering and deriving the linear interpolation error bounds when only a subset of PBFICs is used. The provided theoretical analysis indicates that the necessary number of PBFICs for user-provided precision depends on the range kernel and, for typical Gaussian range kernels, a small percentage (typically less than 4%) of the PBFICs are enough for good approximations.

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