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    Sparse image and signal processing: Wavelets and related geometric multiscale analysis

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    Authors
    Starck, Jean-Luc
    Murtagh, Fionn cc
    Fadili, Jalal
    Affiliation
    Centre d'Etudes Atomiques, Saclay
    Ecole Nationale Supérieure de Caen
    University of Derby
    Issue Date
    2016-01
    
    Metadata
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    Abstract
    This thoroughly updated new edition presents state-of-the-art sparse and multiscale image and signal processing. It covers linear multiscale geometric transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Along with an up-to-the-minute description of required computation, it covers the latest results in inverse problem solving and regularization, sparse signal decomposition, blind source separation, in-painting, and compressed sensing. New chapters and sections cover multiscale geometric transforms for three-dimensional data (data cubes), data on the sphere (geo-located data), dictionary learning, and nonnegative matrix factorization. The authors wed theory and practice in examining applications in areas such as astronomy, including recent results from the European Space Agency's Herschel mission, biology, fusion physics, cold dark matter simulation, medical MRI, digital media, and forensics. MATLAB® and IDL code, available online at www.SparseSignalRecipes.info, accompany these methods and all applications.
    Citation
    Starck, J., Murtagh, F., Fadili, J. (2016) 'Sparse image and signal processing: Wavelets and related geometric multiscale analysis', Cambridge: Cambridge University Press, 2nd ed.
    Publisher
    Cambridge University Press
    URI
    http://hdl.handle.net/10545/620804
    Additional Links
    http://www.cambridge.org/gb/academic/subjects/computer-science/computer-graphics-image-processing-and-robotics/sparse-image-and-signal-processing-wavelets-and-related-geometric-multiscale-analysis-2nd-edition?format=HB
    Type
    Book
    Language
    en
    ISBN
    9781107088061
    Collections
    Department of Electronics, Computing & Maths

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