No-reference image quality assessment based on deep learning

Yifan Wang; Fan Zhang; Sheng Chang; Xinhong Zhang

doi:10.1117/12.3006137

10 October 2023 No-reference image quality assessment based on deep learning

Yifan Wang, Fan Zhang, Sheng Chang, Xinhong Zhang

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127991E (2023) https://doi.org/10.1117/12.3006137
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Images form the basis of human vision and are an important source of information for both human perception and machine pattern recognition. Since the development of the image quality evaluation field, a large number of image quality evaluation algorithms have emerged. In recent years, deep learning has become a hot area and has also been applied to the image domain. This paper focuses on reference-free image quality evaluation and reviews the no-reference image quality assessment based on deep learning. Firstly, the classification of IQA, technical indexes for IQA algorithm evaluation, and several public IQA databases available online are introduced. Then, several deep learning models applied to NR-IQA are discussed, compared, and evaluated in detail. Finally, an outlook on future research is provided.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yifan Wang, Fan Zhang, Sheng Chang, and Xinhong Zhang "No-reference image quality assessment based on deep learning", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127991E (10 October 2023); https://doi.org/10.1117/12.3006137

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