No-reference Image Quality Assessment Based on Local Maximum Gradient

Jiang Ping; Zhang Jian-zhou

doi:10.11999/JEIT141447

Volume 37 Issue 11

Nov. 2015

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Jiang Ping, Zhang Jian-zhou. No-reference Image Quality Assessment Based on Local Maximum Gradient[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2587-2593. doi: 10.11999/JEIT141447

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Jiang Ping, Zhang Jian-zhou. No-reference Image Quality Assessment Based on Local Maximum Gradient[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2587-2593. doi: 10.11999/JEIT141447

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No-reference Image Quality Assessment Based on Local Maximum Gradient

doi: 10.11999/JEIT141447

Jiang Ping¹,
Zhang Jian-zhou²

1.
2.
(Computer College, Sichuan University, Chengdu 610065, China)

Received Date: 2014-11-20
Rev Recd Date: 2015-07-15
Publish Date: 2015-11-19

Abstract

Abstract

Image Quality Assessment (IQA) is widely used in digital image processing, and No Reference IQA (NR-IQA) has become the research focus recently. This paper proposes an NR-IQA method based on local structure, which chooses strong structure areas by using local gradients, and assesses the quality of image by utilizing the Maximum Local Gradients (MLG) of strong structure areas. The main novelties are: pixel,s quality assessment based on MLG; whole image quality based on strong edge points, quality. The proposed method can assess noise image and blur image at the same time, and the score of the proposed method is smaller when the distortion is more serious. The results show that the proposed no-reference method for the quality prediction of noise and blur images has a comparable performance to the leading metrics available in literature.
- Image quality assessment,
- Gradient mask,
- Gaussian noise,
- Gaussian blur

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References(19)

References

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