Technology of Graphic & Image
|
App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 7
2198-2203,2222

Full-reference video quality assessment combining spatio-temporal features and visual perception

Liu Cong
Kong Guangqian
Duan Xun
Wu Yun
State Key Laboratory of Public Big Data, College of Computer Science & Technology, Guizhou University, Guiyang 550025, China
DOI: 10.19734/j.issn.1001-3695.2022.11.0631

Abstract

Video distortion mainly comes from the degradation of video quality caused by spatial and temporal distortion. Aiming at these two kinds of video quality degradation, this paper proposed a full-reference video quality assessment method STPFVQA combining spatio-temporal features and visual perception. Firstly, the method extracted spatial perceptual features from reference video and distorted video using ResNet50 convolutional network. Secondly, the method feeded the extracted spatial perceptual features into transformer's encoder and decoder to construct the serialization relationship of the video, and at the same time to explore the effect of distortion on the video serialization relationship by comparing the reference video and distorted video. Then, the method sent the output of the transformer to the prediction header to form a frame-level score. Finally, in order to simulate the hysteresis of human visual system perception, this paper obtained the video quality score from the short-term, long-term and global memory effects. To verify the feasibility of the method, this paper conducted experiments on four datasets, respectively LIVE, IVC-IC, CSIQ, and IVPL. The experimental results show that the proposed method is more consistent with the perception of the human visual system. Compared with the state-of-the-art serial dependence model(SDM) on the IVC-IC and CSIQ datasets, the SROCC is 2.6% and 3.1% higher, the KROCC is 6.1% and 7.9% higher, and the PLCC is 2.3% and 5.5% higher.

Foundation Support

国家自然科学基金资助项目(62266011)
贵州省基础研究计划资助项目(黔科合基础-ZK[2022]一般119)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.11.0631
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 7
Section: Technology of Graphic & Image
Pages: 2198-2203,2222
Serial Number: 1001-3695(2023)07-042-2198-06

Publish History

[2023-01-31] Accepted Paper
[2023-07-05] Printed Article

Cite This Article

刘聪, 孔广黔, 段迅, 等. 结合时空特征和视觉感知的全参考视频质量评价 [J]. 计算机应用研究, 2023, 40 (7): 2198-2203,2222. (Liu Cong, Kong Guangqian, Duan Xun, et al. Full-reference video quality assessment combining spatio-temporal features and visual perception [J]. Application Research of Computers, 2023, 40 (7): 2198-2203,2222. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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