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Single Image Super Resolution Using Convolutional Neural Networks for Noisy Images
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Publication Year
2020-10-21
Journal
International Conference on ICT Convergence
Publisher
IEEE Computer Society
Citation
International Conference on ICT Convergence, Vol.2020-October, pp.195-199
Keyword
image denoisingimage restorationimage super-resolution
Mesh Keyword
High quality imagesHigh resolution imageImage restoration problemImage super resolutionsLearning-based approachLow resolution imagesSuper resolution algorithmsTexture components
All Science Classification Codes (ASJC)
Information SystemsComputer Networks and Communications
Abstract
In this paper, we address a problem of image super resolution to obtain a noise-free and high resolution image from a noisy and low resolution image. In recent years, deep learning-based approaches have been achieved a lot of progress to the image restoration problems. However, it is still not trivial to generate a high quality image when the input image is both noisy and low-resolution, because it is difficult to disambiguate the fine texture components from noise components for the input image. In this case, conventional super-resolution algorithms usually amplify the noise along with the details. To deal with this problem, we propose a super-resolution network that is robust to noisy images by constructing multi-modules in parallel architecture. The experimental results show that our proposed network restores a noise-free and rich-texture image from the low-resolution and noisy input image, while other methods fail.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36592
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85098979837&origin=inward
DOI
https://doi.org/10.1109/ictc49870.2020.9289414
Journal URL
http://ieeexplore.ieee.org/xpl/conferences.jsp
Type
Conference
Funding
ACKNOWLEDGEMENT This work was supported by the Ministry of Science and ICT (MSIT), South Korea, under the Information Technology Research Center (ITRC) Support Program supervised by the Institute for Information and Communications Technology Promotion (IITP) under Grant IITP-2020-2018-0-01424.
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Heo,Yong Seok  Image
Heo,Yong Seok 허용석
Department of Electrical and Computer Engineering
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