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http://dx.doi.org/10.3837/tiis.2021.11.010

Blind Quality Metric via Measurement of Contrast, Texture, and Colour in Night-Time Scenario  

Xiao, Shuyan (School of Electrical & Information Engineering, Jiangsu University of Technology)
Tao, Weige (School of Electrical & Information Engineering, Jiangsu University of Technology)
Wang, Yu (School of Electrical & Information Engineering, Jiangsu University of Technology)
Jiang, Ye (School of Computer Science and Information Engineering, HeFei University of Technology)
Qian, Minqian. (School of Computer Science and Information Engineering, HeFei University of Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.15, no.11, 2021 , pp. 4043-4064 More about this Journal
Abstract
Night-time image quality evaluation is an urgent requirement in visual inspection. The lighting environment of night-time results in low brightness, low contrast, loss of detailed information, and colour dissonance of image, which remains a daunting task of delicately evaluating the image quality at night. A new blind quality assessment metric is presented for realistic night-time scenario through a comprehensive consideration of contrast, texture, and colour in this article. To be specific, image blocks' color-gray-difference (CGD) histogram that represents contrast features is computed at first. Next, texture features that are measured by the mean subtracted contrast normalized (MSCN)-weighted local binary pattern (LBP) histogram are calculated. Then statistical features in Lαβ colour space are detected. Finally, the quality prediction model is conducted by the support vector regression (SVR) based on extracted contrast, texture, and colour features. Experiments conducted on NNID, CCRIQ, LIVE-CH, and CID2013 databases indicate that the proposed metric is superior to the compared BIQA metrics.
Keywords
Colour; Contrast; BIQA; Realistic night-time images; Texture;
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