HVS-Based Perception-Driven No-Reference Omnidirectional Image Quality Assessment
Author:
Affiliation:
1. College of Information, Liaoning University, Liaoning, Shenyang, China
2. Department of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/10012124/10002344.pdf?arnumber=10002344
Reference57 articles.
1. Blind Image Quality Assessment Using a Deep Bilinear Convolutional Neural Network
2. Making a “Completely Blind” Image Quality Analyzer
3. Perceptual Quality Assessment of Omnidirectional Images as Moving Camera Videos
4. FSIM: A Feature Similarity Index for Image Quality Assessment
5. Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index
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