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Proceedings Paper

Visual pattern degradation based image quality assessment
Author(s): Jinjian Wu; Leida Li; Guangming Shi; Weisi Lin; Wenfei Wan
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Paper Abstract

In this paper, we introduce a visual pattern degradation based full-reference (FR) image quality assessment (IQA) method. Researches on visual recognition indicate that the human visual system (HVS) is highly adaptive to extract visual structures for scene understanding. Existing structure degradation based IQA methods mainly take local luminance contrast to represent structure, and measure quality as degradation on luminance contrast. In this paper, we suggest that structure includes not only luminance contrast but also orientation information. Therefore, we analyze the orientation characteristic for structure description. Inspired by the orientation selectivity mechanism in the primary visual cortex, we introduce a novel visual pattern to represent the structure of a local region. Then, the quality is measured as the degradations on both luminance contrast and visual pattern. Experimental results on Five benchmark databases demonstrate that the proposed visual pattern can effectively represent visual structure and the proposed IQA method performs better than the existing IQA metrics.

Paper Details

Date Published: 5 August 2015
PDF: 8 pages
Proc. SPIE 9622, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 96220P (5 August 2015); doi: 10.1117/12.2192967
Show Author Affiliations
Jinjian Wu, Xidian Univ. (China)
Leida Li, China Univ. of Mining and Technology (China)
Guangming Shi, Xidian Univ. (China)
Weisi Lin, Nanyang Technological Univ. (Singapore)
Wenfei Wan, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 9622:
2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology
Guangming Shi; Xuelong Li; Bormin Huang, Editor(s)

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