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Laser & Optoelectronics Progress, Volume. 60, Issue 4, 0410001(2023)

Infrared Dim Small Target Detection Method Based on Enhanced Local Contrast

Ming Yuan1,1,2、">*, Yansong Song2、**, Ziqi Zhang2,2、">, Xin Zhao1,1、">, and Bo Zhao2,2、">
Author Affiliations
  • 1College of Electronic Information Engineering, Changchun University of Science and Technology, Changchun 130022, Jilin, China
  • 2Institute of Space Photoelectrics Technology, Changchun University of Science and Technology, Changchun 130022, Jilin,China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (11)
    Equations (21)
    References (20)
    Cited By (1)
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    Figures & Tables(11)
    Traditional local contrast sliding window

    Fig. 1. Traditional local contrast sliding window

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    Overall of proposed algorithm

    Fig. 2. Overall of proposed algorithm

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    Schematic of fast median filtering

    Fig. 3. Schematic of fast median filtering

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    Cyclic structural element

    Fig. 4. Cyclic structural element

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    Splitting sliding window structure

    Fig. 5. Splitting sliding window structure

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    Processing examples of the proposed algorithm. (a) Pretreatment image; (b) local contrast image;

    Fig. 6. Processing examples of the proposed algorithm. (a) Pretreatment image; (b) local contrast image;

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    Detection effects of four algorithms. (a) Original image; (b) ILCM; (c) TOP-HAT; (d) MLCM; (e) proposed algorithm

    Fig. 7. Detection effects of four algorithms. (a) Original image; (b) ILCM; (c) TOP-HAT; (d) MLCM; (e) proposed algorithm

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    • Table 1. SCRG of each algorithm at three scenes

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      Table 1. SCRG of each algorithm at three scenes

      AlgorithmDataset 1Dataset 2Dataset 3
      ILCM1.162011.075610.35458
      TOP-HAT0.2668890.2799751.59188
      MLCM0.7345590.4210351.15711
      Proposed algorithm1.642737.4162510.7065

    • Table 2. BSF of each algorithm at three scenes

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      Table 2. BSF of each algorithm at three scenes

      AlgorithmDataset 1Dataset 2Dataset 3
      ILCM1.115651.011870.64693
      TOP-HAT2.059661.509383.87014
      MLCM0.7738450.532650.987807
      Proposed algorithm2.315211.351456.21517

    • Table 3. Time of each algorithm at three scenes unit: s

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      Table 3. Time of each algorithm at three scenes unit: s

      AlgorithmDataset 1Dataset 2Dataset 3
      ILCM0.18840.18380.1809
      TOP-HAT0.06710.06900.0851
      MLCM0.18240.18490.1808
      Proposed algorithm0.18300.18090.1754

    • Table 4. False alarm rate of each algorithm at three scenes

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      Table 4. False alarm rate of each algorithm at three scenes

      AlgorithmDataset 1Dataset 2Dataset 3
      ILCM0.1330.40.6
      TOP-HAT0.46710.2
      MLCM000.133
      Proposed algorithm000
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    Ming Yuan, Yansong Song, Ziqi Zhang, Xin Zhao, Bo Zhao. Infrared Dim Small Target Detection Method Based on Enhanced Local Contrast[J]. Laser & Optoelectronics Progress, 2023, 60(4): 0410001

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    Paper Information

    Category: Image Processing

    Received: Sep. 22, 2021

    Accepted: Dec. 21, 2021

    Published Online: Feb. 14, 2023

    The Author Email: Yuan Ming (850356084@qq.com), Song Yansong (songyansong2012@126.com)

    DOI:10.3788/LOP212575

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology