Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)

Single Image Super-Resolution Based on Improved WGAN

Authors
Lei Yu, Xiang Long, Chao Tong
Corresponding Author
Lei Yu
Available Online March 2018.
DOI
https://doi.org/10.2991/acaai-18.2018.24How to use a DOI?
Keywords
Super-resolution; WGAN-GP; VGG
Abstract

SRGAN has successfully applied the Generative Adversarial Network to the single image super-resolution reconstruction, which has achieved good results. But the loss function based on feature space in SRGAN objectively sacrifices the pursuit of high peak signal-to-noise-ratio (PSNR), which is the result of a tradeoff. At the same time, Improved Training of Wasserstein GANs makes the training process more stable. We redesign the SRGAN, using VGG16 network for feature extraction, setting discriminator network's working space as feature space, and adding the loss function based on the mean square error of pixel space, then gain more details and high PSNR in the reconstruction at the same time. We use the design of WGAN-GP for reference to make the training more stable.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
Series
Advances in Intelligent Systems Research
Publication Date
March 2018
ISBN
978-94-6252-483-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/acaai-18.2018.24How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lei Yu
AU  - Xiang Long
AU  - Chao Tong
PY  - 2018/03
DA  - 2018/03
TI  - Single Image Super-Resolution Based on Improved WGAN
BT  - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
PB  - Atlantis Press
SP  - 101
EP  - 104
SN  - 1951-6851
UR  - https://doi.org/10.2991/acaai-18.2018.24
DO  - https://doi.org/10.2991/acaai-18.2018.24
ID  - Yu2018/03
ER  -