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    Spectrum decomposition for image/signal coding

    Access Status
    Fulltext not available
    Authors
    Lin, Jianyu
    Smith, M.
    Date
    2013
    Type
    Journal Article
    
    Metadata
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    Citation
    Lin, Jianyu and Smith, Mark T.J. 2013. Spectrum decomposition for image/signal coding. IEEE Transactions on Signal Processing. 61 (5): pp. 1065-1071.
    Source Title
    IEEE Transactions on Signal Processing
    DOI
    10.1109/TSP.2012.2231680
    ISSN
    1053-587X
    URI
    http://hdl.handle.net/20.500.11937/33536
    Collection
    • Curtin Research Publications
    Abstract

    In conventional subband/wavelet image coding, the subband decomposition is performed on the spatial-domain image. Here, we introduce a novel decomposition where the subband decomposition is performed on the global DCT spectrum of the image. That is, the two-dimensional spectrum rather than the image is represented by a sum of basis functions, each weighted by the transform coefficients. The distinct features of this decomposition are analyzed from a transform perspective. This spectral subband decomposition is then used as the basis for a new image coder, building on the condensed wavelet packet (CWP) algorithm. Ironically, this new method is shown to have lower arithmetic complexity than conventional subband/wavelet coders that directly decompose a time or spatial domain signal. Comparisons of the new method against conventional subband/wavelet coders that use the popular 9/7 dyadic decomposition, condensed wavelet packets, and generalized lapped orthogonal transforms, show that the new method has lower complexity and higher compression performance.

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