ijicic-140525.pdf (1.32 MB)
Video resolution enhancement using deep neural networks and intensity based registrations
journal contribution
posted on 2019-06-10, 12:51 authored by Gholamreza Anbarjafari© 2018 ICIC International. Thanks to the recent rapid improvements made to the maximum possible resolution of display devices, higher qualities of experience have been made possible, which necessitates either producing and transmitting considerably higher volumes of data or super-resolving lower-resolution contents at the display side, where the former might not be practically feasible. Therefore, aiming at the latter, this paper proposes a novel super-resolution technique, which takes advantage of convolutional neural networks. Each image is registered into a window consisting of two frames, the second one standing for the reference image, using various intensity-based techniques, which have been tested and compared throughout the paper. According to the experimental results, the proposed method leads to substantial enhancements in the quality of the super-resolved images, compared with the state-of-the-art techniques introduced within the existing literature. On the Akiyo video sequence, on average, the result possesses 5.38dB higher PSNR values than those of the Vandewalle registration technique, with structure adaptive normalised convolution being utilized as the reconstruction approach.
Funding
This work has been partially supported by the Estonian Research Council Grant (PUT638) and the Scientific and Technological Research Council of Turkey (TUBTAK) (Project 1001-116E097).
History
School
- Loughborough University London
Published in
International Journal of Innovative Computing, Information and ControlVolume
14Issue
5Pages
1969 - 1976Citation
ANBARJAFARI, G., 2018. Video resolution enhancement using deep neural networks and intensity based registrations. International Journal of Innovative Computing, Information and Control, 14(5), pp. 1969 - 1976.Publisher
© ICIC InternationalVersion
- VoR (Version of Record)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2018-10-01Notes
This paper was published in the journal International Journal of Innovative Computing, Information and Control and the definitive published version is available at https://doi.org/10.24507/ijicic.14.05.1969ISSN
1349-4198Publisher version
Language
- en
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