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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 7
2190-2195

Dual direction complementary learning network based defocus blur detection

Zhang Guangqiang1
Zheng Jinjin1
Feng Sui1
Su Tiancheng1
Zhou Hongjun2
1. Dept. of Precision Machinery & Precision Instrumentations, University of Science & Technology of China, Hefei 230026, China
2. National Synchrotron Radiation Laboratory, Hefei 230029, China
DOI: 10.19734/j.issn.1001-3695.2021.12.0683

Abstract

Many challenging problems exist, such as, missing boundary details, misclassifying homogeneous clear areas and the difficulty of dealing with low illuminance regions, in defocus blur detection(DBD). To solve these issues, this paper proposed a dual direction complementary learning network(DDCLNet), via dual direction learning and fusing hierarchical complementary features to obtain high quality results. The network consisted of residual modules, a dual direction complementary decoder subnet(DDCDS) and a fusion correction decoder subnet(FCDS). Residual modules extracted hierarchical features of the source images. DDCDS simultaneously learned clear and blurry information to complement each other. FCDS fused complementary features. In addition, all decoder subnets utilized the supervision mechanism to guide the network to learn efficiently. The F-measure increases by 1.1%, 0.1%, 1.8% on three public datasets than other methods and the detection speed reaches 26.618 fps, which surpasses exiting methods. DDCLNet can effectively dig out the information of the hierarchical features and complementary labels, to obtain high quality detection results fast.

Foundation Support

国家自然科学基金联合基金资助项目(GG2090090072,U1332130,U1713206)
国家自然基金重大仪器专项资助项目(61727809)
安徽省重点研究与开发计划资助项目(1704a0902051)
国家重点研发资助项目(SQ2019YFC010463)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.12.0683
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 7
Section: Technology of Graphic & Image
Pages: 2190-2195
Serial Number: 1001-3695(2022)07-044-2190-06

Publish History

[2022-03-09] Accepted Paper
[2022-07-05] Printed Article

Cite This Article

张广强, 郑津津, 丰穗, 等. 基于双向互补学习网络的散焦模糊检测 [J]. 计算机应用研究, 2022, 39 (7): 2190-2195. (Zhang Guangqiang, Zheng Jinjin, Feng Sui, et al. Dual direction complementary learning network based defocus blur detection [J]. Application Research of Computers, 2022, 39 (7): 2190-2195. )

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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