• DocumentCode
    1141009
  • Title

    Deblurring subject to nonnegativity constraints

  • Author

    Snyder, Donald L. ; Schulz, Timothy J. ; Sullivan, Joseph A O

  • Author_Institution
    Dept. of Electr. Eng., Washington Univ., St. Louis, MO, USA
  • Volume
    40
  • Issue
    5
  • fYear
    1992
  • fDate
    5/1/1992 12:00:00 AM
  • Firstpage
    1143
  • Lastpage
    1150
  • Abstract
    Csiszar´s I-divergence is used as a discrepancy measure for deblurring subject to the constraint that all functions involved are nonnegative. An iterative algorithm is proposed for minimizing this measure. It is shown that every function in the sequence is nonnegative and the sequence converges monotonically to a global minimum. Other properties of the algorithm are shown, including lower bounds on the improvement in the I-divergence at each step of the algorithm and on the difference between the I-difference at step k and at the limit point. A method for regularizing the solution is proposed
  • Keywords
    iterative methods; picture processing; I-divergence; deblurring; discrepancy measure; image reconstruction; iterative algorithm; nonnegativity constraints; regularisation; Deconvolution; Integral equations; Iterative algorithms; Iterative methods; Kernel; Laboratories; Stochastic resonance;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.134477
  • Filename
    134477