Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 4
1256-1260,1274

Video image super-resolution reconstruction method based on convolutional neural network

Liu Cun
Li Yuanxiang
Zhou Yongjun
Luo Jianhua
School of Aeronautics & Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China
DOI: 10.19734/j.issn.1001-3695.2017.10.1020

Abstract

In order to further improve the performance of video image super-resolution reconstruction and study the reconstruction of spatial resolution of video images by using the characteristics of convolution neural network, this paper proposed a video image reconstruction model based on convolution neural network. The model adopted the pre-training strategy to initialize the parameters. And it carried out the training processing both on the spatial and temporal dimensions of the multi-frame video images at the same time. It extracted the characteristics of the main motion information, learnt and made full use of the information inter the frames for improved performance. And it used the adaptive motion compensation algorithm to optimize the output of the channel to obtain the reconstructed center frame image with high resolution. The experimental results show that the average of objective evaluation indexes for video image reconstruction improves with a rather clear margin(PSNR+0.4 dB/SSIM+0.02), and the edge of the fuzzy phenomenon in video reconstruction image for the subjective visual effect is effectively reduced. Compared with other traditional algorithms, it both obviously improved the evaluation of the objective indexes and subjective visual effect of the reconstructed image. Providing a novel architecture based on convolution neural network for video image super-resolution, which provides an exploration for the further study of video image super-resolution reconstruction based on the deep learning method.

Foundation Support

国家自然科学基金资助项目(11672183)
上海市军民融合专项资助项目(2016GFZ-GB02-342)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.10.1020
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 4
Section: Technology of Graphic & Image
Pages: 1256-1260,1274
Serial Number: 1001-3695(2019)04-066-1256-05

Publish History

[2019-04-05] Printed Article

Cite This Article

刘村, 李元祥, 周拥军, 等. 基于卷积神经网络的视频图像超分辨率重建方法 [J]. 计算机应用研究, 2019, 36 (4): 1256-1260,1274. (Liu Cun, Li Yuanxiang, Zhou Yongjun, et al. Video image super-resolution reconstruction method based on convolutional neural network [J]. Application Research of Computers, 2019, 36 (4): 1256-1260,1274. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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