Superresolution Reconstruction of Video Based on Efficient Subpixel Convolutional Neural Network for Urban Computing
Joint Authors
Shen, Jie
Du, Xinyu
Xiong, Yunbo
Xu, Mengxi
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-11
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
Video surveillance is an important data source of urban computing and intelligence.
The low resolution of many existing video surveillance devices affects the efficiency of urban computing and intelligence.
Therefore, improving the resolution of video surveillance is one of the important tasks of urban computing and intelligence.
In this paper, the resolution of video is improved by superresolution reconstruction based on a learning method.
Different from the superresolution reconstruction of static images, the superresolution reconstruction of video is characterized by the application of motion information.
However, there are few studies in this area so far.
Aimed at fully exploring motion information to improve the superresolution of video, this paper proposes a superresolution reconstruction method based on an efficient subpixel convolutional neural network, where the optical flow is introduced in the deep learning network.
Fusing the optical flow features between successive frames can compensate for information in frames and generate high-quality superresolution results.
In addition, in order to improve the superresolution, a superpixel convolution layer is added after the deep convolution network.
Finally, experimental evaluations demonstrate the satisfying performance of our method compared with previous methods and other deep learning networks; our method is more efficient.
American Psychological Association (APA)
Shen, Jie& Xu, Mengxi& Du, Xinyu& Xiong, Yunbo. 2020. Superresolution Reconstruction of Video Based on Efficient Subpixel Convolutional Neural Network for Urban Computing. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1214792
Modern Language Association (MLA)
Shen, Jie…[et al.]. Superresolution Reconstruction of Video Based on Efficient Subpixel Convolutional Neural Network for Urban Computing. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1214792
American Medical Association (AMA)
Shen, Jie& Xu, Mengxi& Du, Xinyu& Xiong, Yunbo. Superresolution Reconstruction of Video Based on Efficient Subpixel Convolutional Neural Network for Urban Computing. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1214792
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214792