Domain decomposition methods for compressed sensing

Massimo Fornasier, Andreas Langer, Carola-Bibiane Schönlieb

    Research output: Contribution to conferencePaper

    25 Downloads (Pure)

    Abstract

    We present several domain decomposition algorithms for sequential and parallel minimization of functionals formed by a discrepancy term with respect to data and total variation constraints. The convergence properties of the algorithms are analyzed. We provide several numerical experiments, showing the successful application of the algorithms for the restoration 1D and 2D signals in interpolation/inpainting problems respectively, and in a compressed sensing problem, for recovering piecewise constant medical-type images from partial Fourier ensembles.
    Original languageEnglish
    Publication statusPublished - 22 May 2009
    EventInternational Conference on SAMPling Theory and Applications - Marseille, France
    Duration: 18 May 200922 May 2009

    Conference

    ConferenceInternational Conference on SAMPling Theory and Applications
    Abbreviated titleSAMPTA09
    Country/TerritoryFrance
    CityMarseille
    Period18/05/0922/05/09

    Bibliographical note

    4 pages

    Keywords

    • math.NA
    • 65K10, 65N55, 65N21, 65Y05, 90C25, 52A41, 49M30, 49M27, 68U10

    Fingerprint

    Dive into the research topics of 'Domain decomposition methods for compressed sensing'. Together they form a unique fingerprint.

    Cite this