期刊
IEEE TRANSACTIONS ON IMAGE PROCESSING
卷 27, 期 9, 页码 4516-4528出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2018.2839890
关键词
Image quality assessment (IQA); screen content images (SCIs); Gabor feature
资金
- National Natural Science Foundation of China [61401167, 61372107, 61602191]
- Natural Science Foundation of Fujian Province [2016J01308, 2017J05103]
- Fujian-100 Talented People Program
- High-level Talent Innovation Program of Quanzhou City [2017G027]
- Promotion Program for Young and Middle-aged Teacher in Science and Technology Research of Huaqiao University [ZQN-YX403, ZQN-PY418]
- High-Level Talent Project Foundation of Huaqiao University [14BS201, 14BS204, 16BS108]
In this paper, an accurate and efficient full-reference image quality assessment (IQA) model using the extracted Gabor features, called Gabor feature-based model (GFM), is proposed for conducting objective evaluation of screen content images (SCIs). It is well-known that the Gabor filters are highly consistent with the response of the human visual system (HVS), and the HVS is highly sensitive to the edge information. Based on these facts, the imaginary part of the Gabor filter that has odd symmetry and yields edge detection is exploited to the luminance of the reference and distorted SCI for extracting their Gabor features, respectively. The local similarities of the extracted Gabor features and two chrominance components, recorded in the LMN color space, are then measured independently. Finally, the Gabor-feature pooling strategy is employed to combine these measurements and generate the final evaluation score. Experimental simulation results obtained from two large SCI databases have shown that the proposed GFM model not only yields a higher consistency with the human perception on the assessment of SCIs but also requires a lower computational complexity, compared with that of classical and state-of-the-art IQA models.(1)
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