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
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;
Conference_Titel :
Electrical and Computer Engineering, 1998. IEEE Canadian Conference on
Conference_Location :
Waterloo, Ont.
Print_ISBN :
0-7803-4314-X
DOI :
10.1109/CCECE.1998.682709