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Deep convolution network for surveillance records super-resolution

文献类型：期刊论文

作者Shamsolmoali, Pourya1,2; Zareapoor, Masoumeh1; Jain, Deepak Kumar3; Jain, Vinay Kumar4; Yang, Jie1
刊名MULTIMEDIA TOOLS AND APPLICATIONS
出版日期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
DOI10.1007/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 Dissimilar to the outdated methods which operate components individually, our model performs combined optimization for all the layers.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
WOS记录号WOS:000482419900002
出版者SPRINGER
源URL[http://ir.ia.ac.cn/handle/173211/27226]  
专题离退休人员
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.

入库方式： OAI收割

来源：自动化研究所

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