Hierarchical Feature Extraction Assisted with Visual Saliency for Image Quality Assessment
Joint Authors
Ding, Yong
Deng, Ruizhe
Zhao, Yang
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-03
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Image quality assessment (IQA) is desired to evaluate the perceptual quality of an image in a manner consistent with subjective rating.
Considering the characteristics of hierarchical visual cortex, a novel full reference IQA method is proposed in this paper.
Quality-aware features that human visual system is sensitive to are extracted to describe image quality comprehensively.
Concretely, log Gabor filters and local tetra patterns are employed to capture spatial frequency and local texture features, which are attractive to the primary and secondary visual cortex, respectively.
Moreover, images are enhanced before feature extraction with the assistance of visual saliency maps since visual attention affects human evaluation of image quality.
The similarities between the features extracted from distorted image and corresponding reference images are synthesized and mapped into an objective quality score by support vector regression.
Experiments conducted on four public IQA databases show that the proposed method outperforms other state-of-the-art methods in terms of both accuracy and robustness; that is, it is highly consistent with subjective evaluation and is robust across different databases.
American Psychological Association (APA)
Deng, Ruizhe& Zhao, Yang& Ding, Yong. 2017. Hierarchical Feature Extraction Assisted with Visual Saliency for Image Quality Assessment. Journal of Engineering،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1175157
Modern Language Association (MLA)
Deng, Ruizhe…[et al.]. Hierarchical Feature Extraction Assisted with Visual Saliency for Image Quality Assessment. Journal of Engineering No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1175157
American Medical Association (AMA)
Deng, Ruizhe& Zhao, Yang& Ding, Yong. Hierarchical Feature Extraction Assisted with Visual Saliency for Image Quality Assessment. Journal of Engineering. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1175157
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175157