Blind Image Quality Assessment of Natural Distorted Image Based on Generative Adversarial Networks

Blind Image Quality Assessment of Natural Distorted Image Based on Generative Adversarial Networks

Most existing image quality assessment (IQA) methods focus on improving the performance of synthetic distorted images. Although these methods perform well on the synthetic distorted IQA database, once they are applied to the natural distorted database, the performance will severely decrease. In this...

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Bibliographic Details
Main Authors: Hongtao Yang, Ping Shi, Dixiu Zhong, Da Pan, Zefeng Ying
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Generative adversarial networks
deep learning
image quality assessment
no-reference/blind image quality assessment
natural distorted image
Online Access:https://ieeexplore.ieee.org/document/8918423/

Internet

https://ieeexplore.ieee.org/document/8918423/

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