Acta Optica Sinica, Volume. 40, Issue 11, 1110001(2020)

Infrared and Visible Image Fusion Method Based on Multiscale Low-Rank Decomposition

Chaoqi Chen, Xiangchao Meng*, Feng Shao, and Randi Fu
Author Affiliations
  • Faculty of Information Science and Engineering, Ningbo University, Ningbo, Zhejiang 315211, China
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    Figures & Tables(10)
    Flowchart of the proposed fusion method
    Schematic diagram of multiscale low rank decomposition model
    Schematic diagram of infrared image decomposition in Nato_camp
    Saliency images examples of infrared and visible images obtained by 16×16 low-rank block decomposition. (a) Saliency part of the infrared image Tv_3; (b) saliency part of the visible image Tr_3; (c) pixel distribution of infrared and visible images in the same line
    Image fusion results based on 16×16 low rank block decomposition. (a) Fused image F3; (b) pixel distribution of the fused image
    Fusion results in Nato_camp. (a) Visible image; (b) infrared image; (c) ResNet50 method; (d) CNN method; (e) MISF method; (f) GTF method; (g) FPDE method; (h) proposed method
    Fusion results in Bunker. (a) Visible image; (b) infrared image; (c) ResNet50 method; (d) CNN method; (e) MISF method; (f) GTF method; (g) FPDE method; (h) proposed method
    Fusion results in Kaptein_1123. (a) Visible image; (b) infrared image; (c) ResNet50 method; (d) CNN method; (e) MISF method; (f) GTF method; (g) FPDE method; (h) proposed method
    Fusion results in street. (a) Visible image; (b) infrared image; (c) ResNet50 method; (d) CNN method; (e) MISF method; (f) GTF method; (g) FPDE method; (h) proposed method
    • Table 1. Quantitative evaluation results of fused images

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      Table 1. Quantitative evaluation results of fused images

      ImageEvaluation indexResNet50CNNMISFGTFFPDEProposed
      QAB/F0.33920.50130.51640.37600.39560.4198
      SSIM0.77880.70710.70720.70060.66510.7140
      Nato_campEN6.24216.87386.70466.67786.77206.8827
      SF6.45339.909210.39428.507811.451411.7740
      SD22.714231.742235.287426.862332.378840.6756
      QAB/F0.30830.51080.66300.37750.20980.5434
      SSIM0.67180.64310.63850.61640.50280.6734
      BunkerEN6.72185.75746.86496.62045.87366.6752
      SF7.646412.216112.24589.446110.953911.1145
      SD25.931137.324837.148329.776419.361238.2326
      QAB/F0.32990.70080.70860.48000.47970.6211
      SSIM0.65090.62480.62490.63330.63490.6542
      Kaptein_1123EN6.54687.47237.46996.77996.87127.4812
      SF11.322314.598814.864913.079213.128311.9718
      SD32.183941.290345.926430.744128.800542.6900
      QAB/F0.38310.59810.56480.28290.48810.4997
      SSIM0.67960.72200.70630.70370.68980.7320
      StreetEN5.93217.19777.06796.95816.95157.2832
      SF6.93808.22108.77746.48018.99398.8204
      SD21.233852.241340.496838.172940.528457.0357
      QAB/F0.35200.60830.61500.40080.42860.5985
      SSIM0.73030.71220.69940.70200.65610.7440
      Average index of 25 imagesEN6.19526.75957.07756.63536.58727.1726
      SF8.938010.552311.11379.214012.423712.5216
      SD22.233842.289640.267731.579132.025743.0716
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    Chaoqi Chen, Xiangchao Meng, Feng Shao, Randi Fu. Infrared and Visible Image Fusion Method Based on Multiscale Low-Rank Decomposition[J]. Acta Optica Sinica, 2020, 40(11): 1110001

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    Paper Information

    Category: Image Processing

    Received: Jan. 17, 2020

    Accepted: Feb. 27, 2020

    Published Online: Jun. 10, 2020

    The Author Email: Meng Xiangchao (mengxiangchao@nbu.edu.cn)

    DOI:10.3788/AOS202040.1110001

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