Blind image quality prediction by exploiting multi-level deep representations-Reference-Cited by-同舟云学术

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Blind image quality prediction by exploiting multi-level deep representations

Published:2018-09 Issue: Volume:81 Page:432-442
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Gao Fei^ORCID,Yu Jun,Zhu Suguo,Huang Qingming,Tian Qi

Funder

National Natural Science Foundation of China

Zhejiang Provincial Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference60 articles.

1. Non-distortion-specific no-reference image quality assessment: a survey;Manap;Inf. Sci.,2015

2. Image quality assessment based on multiscale geometric analysis;Gao;IEEE Trans. Image Process.,2009

3. The application of visual saliency models in objective image quality assessment: a statistical evaluation;Zhang;IEEE Trans. Neural Netw. Learn. Syst.,2016

4. Image quality assessment using similar scene as reference;Liang,2016

5. Massive online crowdsourced study of subjective and objective picture quality;Ghadiyaram;IEEE Trans. Image Process.,2015

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