Signal decomposition and coding using a multiresolution transform

    Authors

    Q. Memon;T. Kasparis

    Comments

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    Abbreviated Journal Title

    Int. J. Syst. Sci.

    Keywords

    Automation & Control Systems; Computer Science, Theory & Methods; Operations Research & Management Science

    Abstract

    Signal representation and data coding for one and multidimensional signals have recently received considerable attention due to their importance to several modern technologies. Many useful contributions have been reported that employ wavelets and transform methods. Block transforms, particularly the discrete cosine transform, have been used in image-video coding. Signal decomposition has widely been used in conjunction with the discrete cosine transform for signal compression. In this paper, we explore the approximate trigonometric expansions for the purpose of signal decomposition and coding. Specifically, we give system interpretation to the approximate Fourier expansion using harmonic analysis. Furthermore, we apply the approximate trigonometric expansions to multispectral imagery, and investigate the potential of adaptive coding using blocks of images. The variable length basis functions computed by varying the user-defined parameter of the approximate trigonometric expansions are used for adaptive transform coding of images. Based on signal statistics, the proposed algorithm switches between a transform coder and a subband coder. It is shown that these expansions can be implemented by fast Fourier transform algorithm. Sample results far representing multidimensional signals ave given to illustrate the efficiency of the proposed method. For comparison purposes, the results will be compared with techniques using block discrete cosine transform.

    Journal Title

    International Journal of Systems Science

    Volume

    29

    Issue/Number

    2

    Publication Date

    1-1-1998

    Document Type

    Article

    Language

    English

    First Page

    111

    Last Page

    120

    WOS Identifier

    WOS:000072109500003

    ISSN

    0020-7721

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