Blind image quality assessment based on natural statistics of double-opponency
One of the challenges in image quality assessment (IQA) is to determine the quality score without the presence of the reference image. In this paper, the authors proposed a no-reference image quality assessment method based on the natural statistics of double opponent (DO) cells. It utilizes the sta...
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| Main Authors: | , |
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| Format: | text |
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Animo Repository
2018
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| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/2003 |
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| Institution: | De La Salle University |
| Summary: | One of the challenges in image quality assessment (IQA) is to determine the quality score without the presence of the reference image. In this paper, the authors proposed a no-reference image quality assessment method based on the natural statistics of double opponent (DO) cells. It utilizes the statistical modeling of the three opponency channels using the generalized Gaussian distribution (GGD) and asymmetric generalized Gaussian distribution (AGGD). The parameters of GGD and AGGD are then applied to feedforward neural network to predict the image quality. Result shows that for any opposing channels, its natural statistics parameters when applied to feedforward neural network can achieve satisfactory prediction of image quality. © 2018 Fuji Technology Press.All Rights Reserved. |
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