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    Fast eigenspace decomposition of correlated images

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    http://hdl.handle.net/10217/619
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    Abstract
    We present a computationally efficient algorithm for the eigenspace decomposition of correlated images. Our approach is motivated by the fact that for a planar rotation of a two-dimensional (2-D) image, analytical expressions can be given for the eigendecomposition, based on the theory of circulant matrices. These analytical expressions turn out to be good first approximations of the eigendecomposition, even for three-dimensional (3-D) objects rotated about a single axis. In addition, the theory of circulant matrices yields good approximations to the eigendecomposition for images that result ...
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    Author(s)
    Balakrishnan, Venkataramanan; Maciejewski, Anthony A.; Chang, Chu-Yin

    Date Issued
    2000
    Format
    born digital; articles
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    • Faculty Publications - Department of Electrical and Computer Engineering

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