Visual pattern degradation based image quality assessment

Jinjian Wu; Leida Li; Guangming Shi; Weisi Lin; Wenfei Wan

doi:10.1117/12.2192967

5 August 2015 Visual pattern degradation based image quality assessment

Jinjian Wu, Leida Li, Guangming Shi, Weisi Lin, Wenfei Wan

Proceedings Volume 9622, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology; 96220P (2015) https://doi.org/10.1117/12.2192967
Event: International Conference on Optical Instruments and Technology 2015, 2015, Beijing, China

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.

Citation Download Citation

Jinjian Wu, Leida Li, Guangming Shi, Weisi Lin, and Wenfei Wan "Visual pattern degradation based image quality assessment", Proc. SPIE 9622, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 96220P (5 August 2015); https://doi.org/10.1117/12.2192967

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