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Acta Photonica Sinica, Volume. 49, Issue 4, 0410001(2020)

Infrared and Low-light-level Visible Light Enhancement Image Fusion Method Based on Latent Low-rank Representation and Composite Filtering

Ze-tao JIANG1... Qi JIANG1,*, Yong-song HUANG1 and Shao-qin ZHANG2 |Show fewer author(s)
Author Affiliations
  • 1Guangxi Key Laboratory of Image and Graphic Intelligent Processing, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China
  • 2Nanchang Hangkong University, Nangchang 330063, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (10)
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    References (22)
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    Figures & Tables(10)
    Latent low-rank representation and compound filtering fusion algorithm process

    Fig. 1. Latent low-rank representation and compound filtering fusion algorithm process

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    Enhanced low-light images comparison

    Fig. 2. Enhanced low-light images comparison

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    Proposed decomposition method process

    Fig. 3. Proposed decomposition method process

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    Proposed decomposition method effect

    Fig. 4. Proposed decomposition method effect

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    The first group of fusion image comparison

    Fig. 5. The first group of fusion image comparison

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    The second group of fusion image comparison

    Fig. 6. The second group of fusion image comparison

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    The third group of fusion image comparison

    Fig. 7. The third group of fusion image comparison

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    • Table 1. The first group of objective evaluation indexes for fused images

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      Table 1. The first group of objective evaluation indexes for fused images

      MethodMIIESDAGSF
      Ref.[25]1.838 26.828 431.209 75.600 420.228 9
      Ref.[26]1.879 77.101 837.257 84.569 019.278 7
      Ref.[18]1.820 46.553 029.716 13.456 414.558 4
      Proposed method without low-light visible light enhancement1.856 06.807 433.334 95.456 424.676 3
      Proposed method with low-light visible light enhancement1.941 97.223 944.667 79.461 739.425 3

    • Table 2. The second group of objective evaluation indexes for fused images

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      Table 2. The second group of objective evaluation indexes for fused images

      MethodMIIESDAGSF
      Ref.[25]1.853 96.764 035.175 03.522 314.042 7
      Ref.[26]1.911 96.707 237.048 73.529 721.152 4
      Ref.[18]1.854 06.029 627.485 12.413 515.432 9
      Proposed method without low-light visible light enhancement1.932 16.589 539.078 84.485 031.624 4
      Proposed method with low-light visible light enhancement2.036 36.793 545.320 97.122 644.213 3

    • Table 3. The third group of objective evaluation indexes for fused images

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      Table 3. The third group of objective evaluation indexes for fused images

      MethodMIIESDAGSF
      Ref.[25]1.812 27.217 151.378 14.311 016.416 0
      Ref.[26]1.865 87.100 053.673 33.804 015.279 6
      Ref.[18]1.817 66.701 535.757 02.529 010.599 5
      Proposed method without low-light visible light enhancement1.841 16.936 950.214 34.108 918.587 8
      Proposed method with low-light visible light enhancement1.957 67.502 253.755 28.024 535.706 9
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    Ze-tao JIANG, Qi JIANG, Yong-song HUANG, Shao-qin ZHANG. Infrared and Low-light-level Visible Light Enhancement Image Fusion Method Based on Latent Low-rank Representation and Composite Filtering[J]. Acta Photonica Sinica, 2020, 49(4): 0410001

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    Paper Information

    Category: Image Processing

    Received: Nov. 5, 2019

    Accepted: Dec. 9, 2019

    Published Online: Apr. 24, 2020

    The Author Email: JIANG Qi (597796862@qq.com)

    DOI:10.3788/gzxb20204904.0410001

    Topics

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