Binocular perception based reduced-reference stereo video quality assessment method-Reference-Cited by-同舟云学术

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Binocular perception based reduced-reference stereo video quality assessment method

Published:2016-07 Issue: Volume:38 Page:246-255
ISSN:1047-3203
Container-title:Journal of Visual Communication and Image Representation
language:en
Short-container-title:Journal of Visual Communication and Image Representation

Author:

Yu Mei,Zheng Kaihui,Jiang Gangyi,Shao Feng,Peng Zongju

Funder

Natural Science Foundation of China

National High-tech R&D Program of China

Natural Science Foundation of Zhejiang Province in China

K.C. Wong Magna Fund

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Media Technology,Signal Processing

Reference28 articles.

1. Overview of the MVC+D 3D video coding standard;Chen;J. Vis. Commun. Image Represent.,2014

2. Depth map coding for view synthesis based on distortion analyses;Shao;IEEE J. Emerg. Select. Topics Circ. Syst.,2014

3. No-reference quality assessment for stereoscopic images based on binocular quality perception;Ryu;IEEE Trans. Circuits Syst. Video Technol.,2014

4. Reduced-reference stereoscopic image quality assessment based on view and disparity zero-watermarks;Zhou;Signal Process. Image Commun.,2014

5. The objective quality assessment of stereo image;Yun;Neurocomputing,2013

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1. No-Reference Quality Assessment of Stereoscopic Video Based on Deep Frequency Perception;Proceedings of the 2nd Workshop on Quality of Experience in Visual Multimedia Applications;2022-10-10

2. Jomodevi: A joint motion and depth visibility prediction algorithm for perceived stereoscopic 3D quality;Signal Processing: Image Communication;2022-10

3. Three-Stream 3D deep CNN for no-Reference stereoscopic video quality assessment;Intelligent Systems with Applications;2022-01

4. Stereo Video Quality Metric Based on Multi-Dimensional Analysis;Entropy;2021-08-30

5. On the practical applications of objective quality metrics for stereoscopic 3D imaging;Applications of Machine Learning 2021;2021-08-01

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