NDLI: Accurate single image super-resolution using cascading dense connections

Content Provider	IET Digital Library
Author	Wei, Wei Feng, Guoqi Zhang, Qi Cui, Dongliang Zhang, Miao Chen, Feng
Abstract	In recent years, deep learning methods, especially deep convolutional neural network, have been successfully applied to the single-image super-resolution (SISR) task. In this Letter, the authors propose an accurate SISR method by introducing cascading dense connections in a very deep network. In detail, they construct the cascading dense network (CDN) to fully make use of the hierarchical features from all the convolutional layers, which implements a cascading mechanism upon the dense connected convolutional layers. The cascading dense connection in the CDN enables short and long paths to be built directly from the output to each layer, alleviating the vanishing-gradient problem of very deep networks. Extensive experiments show that CDN achieves state-of-the-art performance on traditional metrics (PSNR and SSIM). Also, they introduce object recognition as the additional evaluation metric for SISR, which further demonstrates the effectiveness of the authors’ method.
Starting Page	739
Ending Page	742
Page Count	4
ISSN	00135194
Volume Number	55
e-ISSN	1350911X
Issue Number	Issue 13, Jun (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/55/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2019.0392
Journal	Electronics Letters
Publisher Date	2019-05-21
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Accurate Single Image Super-resolution Accurate SISR Method Cascading Dense Connection Cascading Dense Network Cascading Mechanism CDN Computer Vision And Image Processing Technique Convolution Deep Convolutional Neural Network Deep Learning Method Deep Network Dense Connected Convolutional Layer Image Resolution Knowledge Engineering Technique Learning in AI Neural Computing Technique Neural Nets Object Recognition Optical, Image And Video Signal Processing Single-image Super-resolution Task
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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