Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 1
314-320

Filtering illumination style under guidance of noise to achieve semantic segmentation of low-light scenes

Luo Jun1
Xuan Shibin1,2
Liu Jialin1
1. College of Artificial Intelligence, Guangxi Minzu University, Nanning 530006, China
2. Guangxi Key Laboratory of Hybrid Computation & IC Design & Analysis, Nanning 530006, China
DOI: 10.19734/j.issn.1001-3695.2023.06.0285

Abstract

Low-light image segmentation is always the difficulty of image segmentation. The low contrast and high fuzziness caused by low light make this kind of image segmentation much more difficult than general image segmentation. In order to improve the accuracy of semantic segmentation in low light environment, this paper proposed a semantic segmentation model of low light scene with filtering light style under noise guidance(SFIS) according to the characteristics of low-light image. The model comprehensively used signal-to-noise ratio as prior knowledge, and adopted different distance interaction for different noise regions in the image by guiding the self-attention operation in the long distance branch and the feature fusion of long/short distance branches. This paper also further designed an illumination filter, which was a module that further extracted the illumination style information from the overall style of the image. By alternately training the illumination filter and the semantic segmentation model, the lighting style gap between different lighting conditions was gradually reduced, so that the segmentation network could learn illumination invariant features. The proposed model outperforms the previous work on the dataset LLRGBD and achieves the best results. The mIoU on the real dataset LLRGBD-real reaches 66.8%, it shows that the proposed long and short distance branch module and the illumination filter module can effectively improve the semantic segmentation ability of the model in low light environment.

Foundation Support

国家自然科学基金资助项目(61866003)
广西民族大学研究生教育创新计划资助项目(gxun-chxs2021063)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.06.0285
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 1
Section: Technology of Graphic & Image
Pages: 314-320
Serial Number: 1001-3695(2024)01-050-0314-07

Publish History

[2023-10-07] Accepted Paper
[2024-01-05] Printed Article

Cite This Article

罗俊, 宣士斌, 刘家林. 噪声指导下过滤光照风格实现低光照场景的语义分割 [J]. 计算机应用研究, 2024, 41 (1): 314-320. (Luo Jun, Xuan Shibin, Liu Jialin. Filtering illumination style under guidance of noise to achieve semantic segmentation of low-light scenes [J]. Application Research of Computers, 2024, 41 (1): 314-320. )

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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