• Optics and Precision Engineering
  • Vol. 32, Issue 8, 1186 (2024)
Jinhui ZUO1,2, Wenbin XU1,3, Shijie ZHOU4, Daobin SHENG5..., Xiangdong XU7, Zhengqiang LI1,*, Yinghui HAN6, Chunjiang WU4 and Lei ZHANG5|Show fewer author(s)
Author Affiliations
  • 1State Environmental Protection Key Laboratory of Satellite Remote Sensing & State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing000, China
  • 2University of Chinese Academy of Sciences, Beijing100049, China
  • 3Science and Technology on Optical Radiation Laboratory, Beijing Institute of Environmental Characteristics, Beijing100854, China
  • 4School of Information and Software Engineering, University of Electronic Science and Technology , Chengdu610000, China
  • 5Jiangsu Ancline Technology Co, Nantong226000, China
  • 6College of Resources and Environment, University of Chinese Academy of Sciences, Beijing100049, China
  • 7Sichuan Yifang Intelligent Technology Co, Chengdu610054, China
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    DOI: 10.37188/OPE.20243208.1186 Cite this Article
    Jinhui ZUO, Wenbin XU, Shijie ZHOU, Daobin SHENG, Xiangdong XU, Zhengqiang LI, Yinghui HAN, Chunjiang WU, Lei ZHANG. Gas leakage detection based on spatiotemporal information of low contrast infrared images[J]. Optics and Precision Engineering, 2024, 32(8): 1186 Copy Citation Text show less
    Uncooled long-wave infrared imaging system
    Fig. 1. Uncooled long-wave infrared imaging system
    Infrared absorption spectra of Butane
    Fig. 2. Infrared absorption spectra of Butane
    Experimental diagram (Case2)
    Fig. 3. Experimental diagram (Case2)
    Filter results for different methods
    Fig. 4. Filter results for different methods
    Results of different gas leak detection algorithms
    Fig. 5. Results of different gas leak detection algorithms
    Comparison of Invalid probability and Error under different algorithms
    Fig. 6. Comparison of Invalid probability and Error under different algorithms

    算法1:基于低对比度红外图像时空信息的气体泄漏检测

    Input:ft(x,y)

    f¯t(x,y)←Time-domain adaptive inter frame filtering ft(x,y)

    if t<N

    spatiotemporal GMM update (ft_new,α=0.01*e1/N

    else:

    spatiotemporal GMM update (ft_new,αi,t=0.01*match(fi,t)

    end if

    Ft(x,y)←spatiotemporal GMM (f¯t(x,y)

    FFRFCM&GCt(x,y)←FRFCM&GC (Ft(x,y)

    Output:FFRFCM&GCt(x,y)

    Table 1. Basic process of the proposed algorithm
    MethodGolf (0,0.1)Walk (0,0.1)Golf (0,0.05)Walk (0,0.05)
    PSNRSSIMPSNRSSIMPSNRSSIMPSNRSSIM
    Anisotropic filtering22.3010.47821.0800.47926.8290.529725.3150.5487
    Bilateral filtering21.9210.48820.4800.52326.1670.59424.7770.6194
    Inter-frame filtering21.9890.60721.6560.73226.4020.66427.0210.825
    Proposed filtering23.5800.69623.4200.74528.6120.784629.0560.834
    Table 2. Comparison of filtering effects of different methods on HMDB51 dataset
    MethodCase1Case2Case3Case4
    PSNRSSIMPSNRSSIMPSNRSSIMPSNRSSIM
    Anisotropic filtering44.2190.96849.7770.91746.3680.90948.4060.919
    Bilateral filtering39.0830.95841.8550.92542.4740.92940.1370.919
    Inter-frame filtering48.8750.98955.6350.99344.4560.99857.49710.981
    Proposed filtering51.4280.99157.6240.99749.7410.99659.0290.993
    Table 3. Comparison of filtering effects of different methods on measured data
    CaseCase 1Case 2Case 3Case 4
    AccIpErrAccIpErrAccIpErrAccIpErr
    FD81.910.37.886.88.74.584.68.37.181.47.810.8
    GMM85.76.87.591.15.63.389.65.25.288.25.66.2
    ViBe84.88.46.890.26.92.9895.65.485.66.87.6
    LBAdaptive90.24.75.194.82.62.693.63.33.190.64.64.8
    Proposed93.13.13.896.32.31.495.22.22.692.32.55.2
    CaseCase 5Case 6Case 7Case 8
    AccIpErrAccIpErrAccIpErrAccIpErr
    FD84.47.18.581.78.69.783.79.17.291.83.74.5
    GMM88.15.36.687.66.95.590.24.75.194.22.63.2
    ViBe89.85.64.688.56.35.287.66.85.694.63.12.3
    LBAdaptive92.62.25.290.64.25.293.42.6495.41.92.7
    Proposed93.22.64.292.32.94.893.63.23.294.81.63.6
    Table 4. Comparison of detection performance of different algorithms
    Jinhui ZUO, Wenbin XU, Shijie ZHOU, Daobin SHENG, Xiangdong XU, Zhengqiang LI, Yinghui HAN, Chunjiang WU, Lei ZHANG. Gas leakage detection based on spatiotemporal information of low contrast infrared images[J]. Optics and Precision Engineering, 2024, 32(8): 1186
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