• DocumentCode
    1539744
  • Title

    Digital image restoration

  • Author

    Banham, Mark R. ; Katsaggelos, Aggelos K.

  • Author_Institution
    Digital Technol. Res. Lab., Motorola Inc., Schaumburg, IL, USA
  • Volume
    14
  • Issue
    2
  • fYear
    1997
  • fDate
    3/1/1997 12:00:00 AM
  • Firstpage
    24
  • Lastpage
    41
  • Abstract
    The article introduces digital image restoration to the reader who is just beginning in this field, and provides a review and analysis for the reader who may already be well-versed in image restoration. The perspective on the topic is one that comes primarily from work done in the field of signal processing. Thus, many of the techniques and works cited relate to classical signal processing approaches to estimation theory, filtering, and numerical analysis. In particular, the emphasis is placed primarily on digital image restoration algorithms that grow out of an area known as “regularized least squares” methods. It should be noted, however, that digital image restoration is a very broad field, as we discuss, and thus contains many other successful approaches that have been developed from different perspectives, such as optics, astronomy, and medical imaging, just to name a few. In the process of reviewing this topic, we address a number of very important issues in this field that are not typically discussed in the technical literature
  • Keywords
    estimation theory; filtering theory; image restoration; least squares approximations; reviews; astronomy; digital image restoration; digital image restoration algorithms; estimation theory; filtering; medical imaging; numerical analysis; optics; regularized least squares; review; signal processing; Biomedical optical imaging; Digital images; Estimation theory; Filtering theory; Image analysis; Image restoration; Numerical analysis; Optical filters; Signal processing algorithms; Signal restoration;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/79.581363
  • Filename
    581363