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    The Multiplicative Zak Transform, Dimension Reduction, and Wavelet Analysis of LIDAR Data

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    No. of downloads: 387

    Date
    2010
    Author
    Flake, Justin Christopher
    Advisor
    Benedetto, John J
    Czaja, Wojciech
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    Abstract
    This thesis broadly introduces several techniques within the context of timescale analysis. The representation, compression and reconstruction of DEM and LIDAR data types is studied with directional wavelet methods and the wedgelet decomposition. The optimality of the contourlet transform, and then the wedgelet transform is evaluated with a valuable new structural similarity index. Dimension reduction for material classification is conducted with a frame-based kernel pipeline and a spectral-spatial method using wavelet packets. It is shown that these techniques can improve on baseline material classification methods while significantly reducing the amount of data. Finally, the multiplicative Zak transform is modified to allow the study and partial characterization of wavelet frames.
    URI
    http://hdl.handle.net/1903/10889
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