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Article

Enhanced Single Image Super Resolution Method Using Lightweight Multi-Scale Channel Dense Network

1
Department of Convergence IT Engineering, Kyungnam University, Changwon 51767, Korea
2
Department of IT Engineering, Sookmyung Women’s University, Seoul 04310, Korea
3
Intelligent Convergence Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Petros Daras
Sensors 2021, 21(10), 3351; https://doi.org/10.3390/s21103351
Received: 11 April 2021 / Revised: 8 May 2021 / Accepted: 10 May 2021 / Published: 12 May 2021
(This article belongs to the Special Issue Visual Sensor Networks for Object Detection and Tracking)
Super resolution (SR) enables to generate a high-resolution (HR) image from one or more low-resolution (LR) images. Since a variety of CNN models have been recently studied in the areas of computer vision, these approaches have been combined with SR in order to provide higher image restoration. In this paper, we propose a lightweight CNN-based SR method, named multi-scale channel dense network (MCDN). In order to design the proposed network, we extracted the training images from the DIVerse 2K (DIV2K) dataset and investigated the trade-off between the SR accuracy and the network complexity. The experimental results show that the proposed method can significantly reduce the network complexity, such as the number of network parameters and total memory capacity, while maintaining slightly better or similar perceptual quality compared to the previous methods. View Full-Text
Keywords: deep learning; super resolution; convolutional neural network; lightweight neural network deep learning; super resolution; convolutional neural network; lightweight neural network
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MDPI and ACS Style

Lee, Y.; Jun, D.; Kim, B.-G.; Lee, H. Enhanced Single Image Super Resolution Method Using Lightweight Multi-Scale Channel Dense Network. Sensors 2021, 21, 3351. https://doi.org/10.3390/s21103351

AMA Style

Lee Y, Jun D, Kim B-G, Lee H. Enhanced Single Image Super Resolution Method Using Lightweight Multi-Scale Channel Dense Network. Sensors. 2021; 21(10):3351. https://doi.org/10.3390/s21103351

Chicago/Turabian Style

Lee, Yooho, Dongsan Jun, Byung-Gyu Kim, and Hunjoo Lee. 2021. "Enhanced Single Image Super Resolution Method Using Lightweight Multi-Scale Channel Dense Network" Sensors 21, no. 10: 3351. https://doi.org/10.3390/s21103351

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