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    Some invariance properties of the minimum noise fraction transform

    Access Status
    Fulltext not available
    Authors
    Berman, M.
    Phatak, Aloke
    Traylen, A.
    Date
    2012
    Type
    Journal Article
    
    Metadata
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    Citation
    Berman, M. and Phatak, A. and Traylen, A. 2012. Some invariance properties of the minimum noise fraction transform. Chemometrics and Intelligent Laboratory Systems. 117: pp. 189-199.
    Source Title
    Chemometrics and Intelligent Laboratory Systems
    DOI
    10.1016/j.chemolab.2012.02.005
    ISSN
    0169-7439
    School
    Department of Mathematics and Statistics
    URI
    http://hdl.handle.net/20.500.11937/29166
    Collection
    • Curtin Research Publications
    Abstract

    The Minimum Noise Fraction (MNF) transform is widely used in the remote sensing and image processing communities, because it is usually better than the Principal Components (PC) transform at compressing and ordering multispectral and hyperspectral images in terms of image “quality”. The MNF transform is also invariant to invertible (i.e. non-singular) linear transformations of multispectral/hyperspectral data, a property not shared by the PC transform. This general invariance property of the MNF transform is proved. Three examples of the general invariance property are provided and discussed: (i) invariance to scaling, (ii) invariance to certain types of background correction, and (iii) invariance to different types of noise.

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