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No-reference image quality assessment based on the AdaBoost BP neural network in the wavelet domain
Version 2 2023-06-12, 09:05
Version 1 2023-06-09, 17:36
journal contribution
posted on 2023-06-12, 09:05 authored by Junhua Yan, Xuehan Bai, Wanyi Zhang, Yongqi Xiao, Chris ChatwinChris Chatwin, Rupert YoungRupert Young, Phil BirchPhil BirchConsidering the relatively poor robustness of quality scores for different types of distortion and the lack of mechanism for determining distortion types, a no-reference image quality assessment (NR-IQA) method based on the AdaBoost BP Neural Network in Wavelet domain (WABNN) is proposed. A 36-dimensional image feature vector is constructed by extracting natural scene statistics (NSS) features and local information entropy features of the distorted image wavelet sub-band coefficients in three scales. The ABNN classifier is obtained by learning the relationship between image features and distortion types. The ABNN scorer is obtained by learning the relationship between image features and image quality scores. A series of contrast experiments are carried out in the LIVE database and TID2013 database. Experimental results show the high accuracy of the distinguishing distortion type, the high consistency with subjective scores and the high robustness of the method for distorted images. Experiment results also show the independence for the database and the relatively high operation efficiency of this method.
Funding
Science and Technology on Avionics Integration Laboratory and Aeronautical Science Foundation of China (20155552050),; iisp-Visiting Fellow; National Natural Science Foundation of China (61471194; 61705104),; (61471194; 61705104),
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Publication status
- Published
File Version
- Published version
Journal
Journal of Systems Engineering and ElectronicsISSN
1004-4132Publisher
Beijing Institute of Aerospace Information (BIAI)External DOI
Issue
2Volume
30Page range
223-237Department affiliated with
- Engineering and Design Publications
Research groups affiliated with
- Industrial Informatics and Signal Processing Research Group Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2019-04-24First Open Access (FOA) Date
2019-07-03First Compliant Deposit (FCD) Date
2019-04-17Usage metrics
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