Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 4
1250-1255

Solar speckle image deblurring method with weakly supervised based on structural re-parameterization

Deng Linhao1
Jiang Murong1
Yang Lei2
Chen Junyi2
Jin Yahui1
1. School of Information Science & Engineering, Yunnan University, Kunming 650500, China
2. Yunnan Observatories, Chinese Academy of Sciences, Kunming 650216, China
DOI: 10.19734/j.issn.1001-3695.2022.07.0388

Abstract

With the supervised deep learning algorithms, it is prone to generate artifacts when restoring the blurred solar speckle images taken by Yunnan Observatories, and it has a long training time and over-reliance on reference images, this paper proposed a weakly supervised method based on structural reparameterization combined with multi-branch module to reconstruct solar speckle images. Firstly, deblurring model combined single-scale and multi-scale network to design, with constructing multi-branch modules to extract features of different scales, enhanced detailed information, and reduced the generation of artifacts. Secondly, each branch structure re-parameterized to make the reuse of structure parameters runs through the entire feature extraction process. After that, the deblurring model embedded in the weakly supervised training, the blurred image assorted firstly, then the degradation model used to learn different levels of degradation. Constituted paired dataset of corresponding levels, and the deblurring model used to inversely degenerate the dataset to reconstruct solar speckle images. Experimental results show that compared with the existing deblurring method, the proposed method has higher model training efficiency and less dependence on reference images, which can meet the high-resolution reconstruction requirements of solar speckle images.

Foundation Support

国家自然科学基金资助项目(11773073)
云南省高校科技创新团队支持项目(IRTSTYN)
云南大学研究生科研创新基金资助项目(2021Y273)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.07.0388
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 4
Section: Technology of Graphic & Image
Pages: 1250-1255
Serial Number: 1001-3695(2023)04-047-1250-06

Publish History

[2022-10-19] Accepted Paper
[2023-04-05] Printed Article

Cite This Article

邓林浩, 蒋慕蓉, 杨磊, 等. 基于结构重参数化的太阳斑点图像弱监督去模糊方法 [J]. 计算机应用研究, 2023, 40 (4): 1250-1255. (Deng Linhao, Jiang Murong, Yang Lei, et al. Solar speckle image deblurring method with weakly supervised based on structural re-parameterization [J]. Application Research of Computers, 2023, 40 (4): 1250-1255. )

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.

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