TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Blind Quality Metric via Measurement of Contrast, Texture, and Colour in Night-Time Scenario |
| 영문제목(English Title) |
Blind Quality Metric via Measurement of Contrast, Texture, and Colour in Night-Time Scenario |
| 저자(Author) |
Fanqi Meng
Wenying Cheng
Jingdong Wang
Shuyan Xiao
Weige Tao
Yu Wang
Ye Jiang
Minqian. Qian
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| 원문수록처(Citation) |
VOL 15 NO. 11 PP. 4043 ~ 4064 (2021. 11) |
한글내용
(Korean Abstract) |
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영문내용
(English 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. |
| 키워드(Keyword) |
Feature Normalization
Oversampling Techniques
Software Defect Prediction
Semi-supervised Learning
Unbalanced Classification
Colour
Contrast
BIQA
Realistic night-time images
Texture
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| 파일첨부 |
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