• DocumentCode
    2491652
  • Title

    Efficient implementation of image recovery algorithms

  • Author

    Dharanipragada, S. ; Arun, K.S.

  • Author_Institution
    Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA
  • fYear
    1994
  • fDate
    2-5 Oct 1994
  • Firstpage
    177
  • Lastpage
    180
  • Abstract
    Presents an efficient implementation scheme for the Newton algorithm for convex set constrained signal recovery [Dharanipragada and Arun, 1993). The implementation avoids matrix creation, inversion and even storage by exploiting the structure of the operators involved and by using conjugate-gradient iterations within each Newton iteration. The resulting algorithm is thus computation and memory efficient and is well-suited for large scale problems typically arising in image recovery applications. The same implementation scheme can also be effectively used for the POCS algorithm
  • Keywords
    Newton method; conjugate gradient methods; image reconstruction; Newton algorithm; POCS algorithm; conjugate-gradient iterations; convex set constrained signal recovery; efficient implementation scheme; image recovery algorithms; large scale problems; Hilbert space; Image converters; Image reconstruction; Image storage; Large-scale systems; Magnetic resonance imaging; Radar signal processing; Signal processing algorithms; Signal resolution; Tomography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Signal Processing Workshop, 1994., 1994 Sixth IEEE
  • Conference_Location
    Yosemite National Park, CA
  • Print_ISBN
    0-7803-1948-6
  • Type

    conf

  • DOI
    10.1109/DSP.1994.379846
  • Filename
    379846