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Proceedings Paper

Blind image quality assessment with complete pixel-level information
Author(s): Jingtao Xu; Haiqing Du; Luping Yang; Yong Liu
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Paper Abstract

In this paper, we develop a novel method for blind image quality assessment (BIQA) based on image complete pixel level information. First, traditional rotation invariant uniform local binary pattern (LBP) histogram is extracted from grayscale image as perceptual quality aware feature. Second, except for the signs of local pixel differences, the magnitudes of local pixel differences in grayscale image are also encoded by LBP, and the joint histogram between the signs and magnitudes of local pixel differences is also calculated as part of the perceptual feature. Finally, the support vector regression (SVR) is utilized to learn the mapping between the combined perceptual feature and human opinion scores. Experimental results show that the proposed method is highly correlated with human opinion scores and achieves competitive performance with state-of-the-art methods for quality evaluation and distortion classification.

Paper Details

Date Published: 29 August 2016
PDF: 5 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100334X (29 August 2016); doi: 10.1117/12.2244288
Show Author Affiliations
Jingtao Xu, Beijing Univ. of Posts and Telecommunications (China)
Haiqing Du, Beijing Univ. of Posts and Telecommunications (China)
Luping Yang, Beijing Univ. of Posts and Telecommunications (China)
Yong Liu, Beijing Univ. of Posts and Telecommunications (China)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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