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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 3
884-888

Image super-resolution model based on feature fusion and attention mechanism

Pan Zhanhong1
Zhu Jian1
Chi Xiaoyu2
Cai Ruichu1
Chen Bingfeng1
1. School of Computers, Guangdong University of Technology, Guangzhou 510006, China
2. Qingdao Research Institute of Beihang University, Qingdao Shandong 266000, China
DOI: 10.19734/j.issn.1001-3695.2021.07.0288

Abstract

Existing deep learning based single image super-resolution(SISR) models usually improve the fitting ability of the model by increasing the number of network layers, but fail to fully extract and reuse features, leading low quality of reconstructed images. To solve this problem, this paper proposed an image super-resolution model based on feature fusion and attention mechanism. This model used residual in residual(RIR) structure in feature extraction module. The feature extraction module of the network consisted of several residual groups. Each residual group consisted of several residual block. This module implemented local feature fusion in each residual group and global feature fusion between each group. In addition, this model introduced coordinate attention module into each residual block and spatial attention module into each residual group. It verifies that the model is able to fully extract features and reuse features. The final experimental results show that the model is superior to the existing models in objective evaluation indexes and subjective visual effect.

Foundation Support

国家自然科学基金资助项目(61502109,61672502,61702112)
广东省自然科学基金资助项目(2016A030310342)
广东省信息物理融合系统重点实验室开放课题(2016B030301008)
NSFC-广东联合基金资助项目(U1501254)
广东省科技计划项目(2016A040403078,2017B010110015,2017B010110007)
广州市珠江科技新星资助项目(201610010101)
广州市科技计划项目(201604016075,202007040005)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.07.0288
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 3
Section: Technology of Graphic & Image
Pages: 884-888
Serial Number: 1001-3695(2022)03-042-0884-05

Publish History

[2021-11-07] Accepted Paper
[2022-03-05] Printed Article

Cite This Article

盘展鸿, 朱鉴, 迟小羽, 等. 基于特征融合和注意力机制的图像超分辨率模型 [J]. 计算机应用研究, 2022, 39 (3): 884-888. (Pan Zhanhong, Zhu Jian, Chi Xiaoyu, et al. Image super-resolution model based on feature fusion and attention mechanism [J]. Application Research of Computers, 2022, 39 (3): 884-888. )

About the Journal

  • 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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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