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
Link To Document :
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