• Journal of Atmospheric and Environmental Optics
  • Vol. 19, Issue 5, 543 (2024)
SA Yu1,2, ZHANG Shilei1,2, TAN Mei1,2, ZHANG Yinghu1,2..., YANG Yunpeng1,2, MA Xiangyun1,2,* and LI Qifeng1,2,**|Show fewer author(s)
Author Affiliations
  • 1School of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin 300072, China
  • 2Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin 300072, China
  • show less
    DOI: 10.3969/j.issn.1673-6141.2024.05.004 Cite this Article
    Yu SA, Shilei ZHANG, Mei TAN, Yinghu ZHANG, Yunpeng YANG, Xiangyun MA, Qifeng LI. Infrared image denoising method for gas leakage based on transfer learning[J]. Journal of Atmospheric and Environmental Optics, 2024, 19(5): 543 Copy Citation Text show less
    References

    [1] P Narkhede, R Walambe, S Mandaokar et al. Gas detection and identification using multimodal artificial intelligence based sensor fusion. Applied System Innovation, 4, 3(2021).

    [2] H B Wu, L L Kong. Temperature safty monitoring of ethylene cracking furnace tube based on infrared imaging technology. Journal of Atmospheric and Environmental Optics, 10, 46-50(2015).

    [3] M S Jadin, K H Ghazali. Gas leakage detection using thermal imaging technique, 302-306(2014).

    [4] D Cardone, A Merla. New frontiers for applications of thermal infrared imaging devices: Computational psychopshysiology in the neurosciences. Sensors, 17, 1042(2017).

    [5] X M Chi, A S Xiao, L Zhu et al. Research progress of infrared imaging detection technology for gas leakage in petrochemical enterprises. Safety Health & Environment, 21, 1-5(2021).

    [6] F Z Li, Y H Zhao, W Xiang et al. Infrared image mixed noise removal method based on improved NL-means. Infrared and Laser Engineering, 48, 163-173(2019).

    [7] C L Lin, C W Kuo, C C Lai et al. A novel approach to fast noise reduction of infrared image. Infrared Physics & Technology, 54, 1-9(2011).

    [8] J Wang, Y K Zhou, J C Hu et al. Infrared image denoising algorithm based on a rough set approach. Infrared Technology, 43, 44-50(2021).

    [9] X Chen, L Liu, J Z Zhang et al. Infrared image denoising based on the variance-stabilizing transform and the dual-domain filter. Digital Signal Processing, 113, 103012(2021).

    [10] B B Yu. An improved infrared image processing method based on adaptive threshold denoising. EURASIP Journal on Image and Video Processing, 2019, 5(2019).

    [11] E D Wang, P Jiang, X P Li et al. Infrared stripe correction algorithm based on wavelet decomposition and total variation-guided filtering. Journal of the European Optical Society-Rapid Publications, 16, 1(2020).

    [12] X D Kuang, X B Sui, Y Liu et al. Single infrared image enhancement using a deep convolutional neural network. Neurocomputing, 332, 119-128(2019).

    [13] C Sun, M Q Pan, B Zhou et al. Infrared image denoising based on convolutional neural network, 499-502(2018).

    [14] X Z Jian, C Lv, R Z Wang. Nonuniformity correction of single infrared images based on deep filter neural network. Symmetry, 10, 612(2018).

    [15] J X Li, P Zhao, W Fang et al. Cloud detection of Multi-Angle remote sensing image based on deep learning. Journal of Atmospheric and Environmental Optics, 15, 380-392(2020).

    [16] W P Li, X G Yang, C X Li et al. An improved semi-supervised transfer learning method for infrared object detection neural network. Infrared and Laser Engineering, 50, 20200511(2021).

    [17] Y Pathak, P K Shukla, A Tiwari et al. Deep transfer learning-based classification model for COVID-19 disease. IRBM, 43, 87-92(2020).

    Yu SA, Shilei ZHANG, Mei TAN, Yinghu ZHANG, Yunpeng YANG, Xiangyun MA, Qifeng LI. Infrared image denoising method for gas leakage based on transfer learning[J]. Journal of Atmospheric and Environmental Optics, 2024, 19(5): 543
    Download Citation