In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
Technology of Graphic & Image
|
283-287

Image rain removal method based on rain and fog separation processing and multiscale network

Wei Hao
Li Hongru
Deng Guoliang
Zhou Shouhuan
College of Electronics & Information Engineering, Sichuan University, Chengdu 610065, China

Abstract

Rain streaks and fog brought by rain can degrade the quality of images taken outdoors. In order to remove the influence of rain and fog on images, this paper proposed an image derain method based on rain and fog separation processing and multi-scale convolutional neural network. Firstly, it extracted the rain lines and image details to the high frequency layer using guided filtering, while separated the fog and background information to the low frequency layer. Then it constructed a multi-scale convolutional neural network to remove the rain lines in the high frequency layer, and incorporated multiple dense connection modules into the network to improve the accuracy of feature extraction. Secondly, it constructed a lightweight defogging network with multi-layer feature fusion to remove the fog in the low frequency layer, and used the parameter integration structure to avoid estimation of multiple atmospheric scattering model parameters resulting in sub-optimal solutions. Finally, it combined the processed high and low frequency results to restore a clear image. Tested on several synthetic rain and fog datasets as well as on real natural scene images, the qualitative and quantitative results show that the proposed method removes rain and fog while retaining color information well, and improves the image structure similarity by 0.02 to 0.08 and the image peak signal-to-noise ratio by 0.2 to 3.5 dB compared to recent algorithms.

Foundation Support

国家自然科学基金资助项目(61705149)
四川省科技计划资助项目(2021YFG0323)
四川大学博士后交叉学科创新启动基金资助项目(BHJC201911)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.05.0243
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 1
Section: Technology of Graphic & Image
Pages: 283-287
Serial Number: 1001-3695(2023)01-047-0283-05

Publish History

[2022-07-25] Accepted Paper
[2023-01-05] Printed Article

Cite This Article

韦豪, 李洪儒, 邓国亮, 等. 基于雨雾分离处理和多尺度网络的图像去雨方法 [J]. 计算机应用研究, 2023, 40 (1): 283-287. (Wei Hao, Li Hongru, Deng Guoliang, et al. Image rain removal method based on rain and fog separation processing and multiscale network [J]. Application Research of Computers, 2023, 40 (1): 283-287. )

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.


Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)