• DocumentCode
    1457874
  • Title

    Least squares restoration of multichannel images

  • Author

    Galatsanos, Nikolas P. ; Katsaggelos, Aggelos K. ; Chin, Roland T. ; Hillery, Allen D.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA
  • Volume
    39
  • Issue
    10
  • fYear
    1991
  • fDate
    10/1/1991 12:00:00 AM
  • Firstpage
    2222
  • Lastpage
    2236
  • Abstract
    Multichannel restoration using both within- and between-channel deterministic information is considered. A multichannel image is a set of image planes that exhibit cross-plane similarity. Existing optimal restoration filters for single-plane images yield suboptimal results when applied to multichannel images, since between-channel information is not utilized. Multichannel least squares restoration filters are developed using the set theoretic and the constrained optimization approaches. A geometric interpretation of the estimates of both filters is given. Color images (three-channel imagery with red, green, and blue components) are considered. Constraints that capture the within- and between-channel properties of color images are developed. Issues associated with the computation of the two estimates are addressed. A spatially adaptive, multichannel least squares filter that utilizes local within- and between-channel image properties is proposed. Experiments using color images are described
  • Keywords
    filtering and prediction theory; least squares approximations; picture processing; between-channel information; color images; constrained optimization approaches; deterministic information; image restoration; least squares restoration filters; multichannel images; set theoretic approach; within-channel information; Color; Constraint theory; Crosstalk; Image restoration; Image sensors; Information filtering; Information filters; Least squares methods; Signal processing; Signal restoration;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.91180
  • Filename
    91180