Open AccessFull‐reference image quality assessment using statistical local correlation
Author(s) -
Ding Yong,
Wang Shaoze,
Zhang Dong
Publication year - 2014
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2013.3365
Subject(s) - image quality , correlation , metric (unit) , artificial intelligence , quality (philosophy) , pattern recognition (psychology) , quality score , quality assessment , wavelet , image (mathematics) , computer science , statistics , mathematics , computer vision , engineering , geometry , philosophy , operations management , epistemology
A novel full‐reference image quality assessment metric employing statistical local correlation as an indicator for quality quantification is presented. The local correlation is extracted in a wavelet domain and is pooled into an objective quality score. Simulation and testing results demonstrate that the proposed method not only outperforms the other methods in terms of high accuracy of image quality prediction, but also is consistent with the subjective evaluations.