Fusing deep learning and statistical visual features for no-reference image quality assessment-Reference-Cited by-同舟云学术

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Fusing deep learning and statistical visual features for no-reference image quality assessment

Published:2020-07-21 Issue:04 Volume:29 Page:1
ISSN:1017-9909
Container-title:Journal of Electronic Imaging
language:
Short-container-title:J. Electron. Imag.

Author:

Zhang Yin¹,Yan Junhua¹,Du Xuan²,Bai Xuehan³,Zhi Xiyang⁴,Hou Ping³,Ma Yue³

Affiliation:

1. Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics,

2. Shanghai Academy of Spaceflight Technology, Shanghai

3. Nanjing University of Aeronautics and Astronautics, College of Astronautics, Nanjing

4. Harbin Institute of Technology, Research Center for Space Optical Engineering, Harbin

Publisher

SPIE-Intl Soc Optical Eng

Subject

Electrical and Electronic Engineering,Computer Science Applications,Atomic and Molecular Physics, and Optics

Reference37 articles.

1. No-Reference Image Quality Assessment in the Spatial Domain

2. Blind/Referenceless Image Spatial Quality Evaluator

3. Blind Image Quality Assessment Using Joint Statistics of Gradient Magnitude and Laplacian Features

4. No-reference image quality assessment based on high order derivatives

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Successive Approximation Register Analog-to-Digital Converter (SAR ADC) for Biomedical Applications;Active and Passive Electronic Components;2023-01-04

2. LG-IQA: Integration of local and global features for no-reference image quality assessment;Displays;2022-12

3. Asymmetric two-stream network for screen content image quality assessment based on region features;Journal of Electronic Imaging;2022-01-11

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