• DocumentCode
    324153
  • Title

    An information theoretic image-quality measure

  • Author

    Elbadawy, Ossama ; El-Sakka, Mahmoud R. ; Kamel, Mohamed S.

  • Author_Institution
    Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
  • Volume
    1
  • fYear
    1998
  • fDate
    24-28 May 1998
  • Firstpage
    169
  • Abstract
    Lossy image compression techniques aim at encoding images with a minimal representation. During this process, some visually useful information may be lost. Assessing the information loss in decompressed images is not an easy task. In this paper, a new quantitative image-quality measure is introduced. This new measure incorporates information theory into the most commonly used objective criterion (the mean square error). The new measure has been tested by experiments performed on a wide variety of images. The results show an increase in the correlation between subjective rating by human observers and the normalized mean square error after applying the new measure
  • Keywords
    data compression; decoding; image coding; least mean squares methods; correlation; decompressed images; experiments; human observers; image coding; image representation; information loss; information theoretic image-quality measure; lossy image compression; normalized mean square error; objective criterion; subjective rating; Humans; Image coding; Image quality; Information theory; Laboratories; Layout; Machine intelligence; Mean square error methods; Pattern analysis; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering, 1998. IEEE Canadian Conference on
  • Conference_Location
    Waterloo, Ont.
  • ISSN
    0840-7789
  • Print_ISBN
    0-7803-4314-X
  • Type

    conf

  • DOI
    10.1109/CCECE.1998.682709
  • Filename
    682709