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Proceedings Paper

Learning the histogram sequences of generalized local ternary patterns for blind image quality assessment
Author(s): Yaping Yan; Songlin Du; Hongjuan Zhang; Yide Ma
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Paper Abstract

The local binary pattern (LBP) has been proved to be significantly useful and competitive in the application of blind image quality assessment (BIQA). However, LBP is short of magnitude information, limiting its performance to some extent. In this paper, we introduce a novel BIQA method, which uses the proposed generalized local ternary pattern (GLTP) to measure structural degradation. By introducing multi-threshold for the gray-level differences, GLTP can provide more discriminative and stable features. Moreover, GLTP contains magnitude information computed by using the magnitudes of horizontal and vertical first-order derivatives. Experimental results on two subject-rated databases demonstrate that the proposed method outperforms state-of-the-art BIQA models, as well as several representative full reference image quality assessment methods for various types of distortions.

Paper Details

Date Published: 9 December 2015
PDF: 7 pages
Proc. SPIE 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015), 981707 (9 December 2015); doi: 10.1117/12.2228241
Show Author Affiliations
Yaping Yan, Lanzhou Univ. (China)
Songlin Du, Lanzhou Univ. (China)
Hongjuan Zhang, Lanzhou Univ. (China)
Yide Ma, Lanzhou Univ. (China)


Published in SPIE Proceedings Vol. 9817:
Seventh International Conference on Graphic and Image Processing (ICGIP 2015)
Yulin Wang; Xudong Jiang, Editor(s)

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