Paper Info
Title
No-reference image quality assessment using local binary pattern in the wavelet domain.
Abstract
Objective quality assessment metrics that are consistent with human judgments of image quality, play an important role in many image processing applications. No-reference image quality assessment (NR-IQA) algorithms evaluate the quality of distorted images without any information about the reference images. In this paper, we propose an accurate and simple method for NR-IQA. In this method local binary pattern (LBP) operator is first applied to subbands of wavelet decomposed image separately; then histogram of LBP codes is calculated and concatenated to form quality aware features. Finally, support vector regression (SVR) is utilized to map the feature vectors to subjective quality scores. The experimental results for LIVE and TID2008 databases show that our proposed method is highly correlated to the subjective scores, and competitive to state-of-the-art NR-IQA methods.
Year
DOI
Venue
2018
10.1007/s11042-017-4432-4
Multimedia Tools Appl.
Keywords
Field
DocType
No-reference image quality assessment, Local binary pattern, Wavelet, Support vector regression
Histogram,Computer vision,Feature vector,Pattern recognition,Computer science,Local binary patterns,Support vector machine,Image processing,Image quality,Artificial intelligence,Operator (computer programming),Wavelet
Journal
Volume
Issue
ISSN
77
2
1573-7721
Citations 
PageRank 
References 
5
0.38
26
Authors
3
Name
Order
Citations
PageRank
Farshad Rezaie150.38
Mohammad Sadegh Helfroush27011.30
Habibollah Danyali34911.07