Deep convolution network for surveillance records super-resolution

doi:10.1007/s11042-018-5915-7

	Deep convolution network for surveillance records super-resolution
	Shamsolmoali, Pourya 1,2; Zareapoor, Masoumeh 1; Jain, Deepak Kumar 3; Jain, Vinay Kumar 4; Yang, Jie 1
刊名	MULTIMEDIA TOOLS AND APPLICATIONS
	2019-09-01
卷号	78 期号:17 页码:23815-23829
关键词	Super-resolution Convolution neural networks Surveillance records Deep learning
ISSN号	1380-7501
DOI	10.1007/s11042-018-5915-7
通讯作者	Shamsolmoali, Pourya(pshams55@gmail.com) ; Yang, Jie(jieyang@sjtu.edu.cn)
英文摘要	The aim of image super resolution (SR) is to recover low resolution (LR) input image or video to a visually desirable high-resolution (HR) one. The task of identifying an object in surveillance records is interesting, yet challenging due to the low resolution of the video. This paper, proposed a deep learning method for resolution recovery, the low-resolution objects and points in the surveillance records are up-sampled using a deep Convolutional Neural Network (CNN) to avoid problems of image boundary the data padded with zeros. The network is trained and tested on two surveillance datasets. Dissimilar to the outdated methods which operate components individually, our model performs combined optimization for all the layers. The proposed CNN model has a lightweight structure and minimal data pre-processing and computation cost. Testing our model and comparing with advanced techniques, we observed promising results. The code is accessible at https://github.com/Mzareapoor/Super-resolution
WOS关键词	IMAGE SUPERRESOLUTION
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000482419900002
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/27226]
专题	中国科学院自动化研究所
通讯作者	Shamsolmoali, Pourya; Yang, Jie
作者单位	1.Shanghai Jiao Tong Univ, Inst Image Proc & Pattern Recognit, Shanghai, Peoples R China 2.Euromediterranean Ctr Climate Change, Adv Sci Comp Div, Lecce, Italy 3.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 4.Jaypee Univ Engn & Technol, Guna, India
推荐引用方式 GB/T 7714	Shamsolmoali, Pourya,Zareapoor, Masoumeh,Jain, Deepak Kumar,et al. Deep convolution network for surveillance records super-resolution[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2019,78(17):23815-23829.
APA	Shamsolmoali, Pourya,Zareapoor, Masoumeh,Jain, Deepak Kumar,Jain, Vinay Kumar,&Yang, Jie.(2019).Deep convolution network for surveillance records super-resolution.MULTIMEDIA TOOLS AND APPLICATIONS,78(17),23815-23829.
MLA	Shamsolmoali, Pourya,et al."Deep convolution network for surveillance records super-resolution".MULTIMEDIA TOOLS AND APPLICATIONS 78.17(2019):23815-23829.