• Optics and Precision Engineering
  • Vol. 31, Issue 10, 1548 (2023)
Yanchun YANG*, Yongping LI, Jianwu DANG, and Yangping WANG
Author Affiliations
  • School of Electronical and Information Engineering,Lanzhou Jiaotong University, Lanzhou730070,China
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    DOI: 10.37188/OPE.20233110.1548 Cite this Article
    Yanchun YANG, Yongping LI, Jianwu DANG, Yangping WANG. Infrared and visible image fusion based on fast alternating guided filtering and CNN[J]. Optics and Precision Engineering, 2023, 31(10): 1548 Copy Citation Text show less
    FAGF structural model
    Fig. 1. FAGF structural model
    FAGF runtime comparison histogram
    Fig. 2. FAGF runtime comparison histogram
    CNN network model
    Fig. 3. CNN network model
    Algorithm idea block diagram of this paper
    Fig. 4. Algorithm idea block diagram of this paper
    CNN network model in this paper
    Fig. 5. CNN network model in this paper
    Filtering results of RGF, SIR,AGFand FAGF
    Fig. 6. Filtering results of RGF, SIR,AGFand FAGF
    Analysis of RGF,SIR,AGF,FAGF filtering result
    Fig. 7. Analysis of RGF,SIR,AGF,FAGF filtering result
    experimental results
    Fig. 8. experimental results
    Three-dimensional comparative analysis chart of fusion results
    Fig. 9. Three-dimensional comparative analysis chart of fusion results
    Indicator comparison line chart
    Fig. 10. Indicator comparison line chart
    AGFFAGF
    Img10.296 7640.055 198
    Img20.772 9670.143 772
    Img31.051 6520.189 297
    Img40.756 2340.140 659
    Img50.345 3300.055 252
    Img60.663 7860.146 032
    Table 1. FAGF running time comparison
    MethodENSDSFFMI_WVIFAG
    Img1WLS6.643 57.908 80.056 80.323 70.651 36.367 8
    GF6.510 47.149 20.040 70.490 90.444 64.791 5
    VGG6.099 67.382 60.026 90.382 90.487 83.161 7
    RES6.237 57.573 30.039 20.398 80.513 34.550 7
    PIAF6.709 87.998 90.041 50.427 60.756 45.116 5
    FAGF6.915 88.211 40.063 40.577 30.758 36.478 9
    Img2WLS6.138 77.047 10.052 40.357 50.761 63.397 3
    GF6.620 57.994 70.037 00.353 50.735 82.448 3
    VGG5.921 67.146 20.028 70.372 50.726 41.957 8
    RES6.031 97.120 70.044 70.408 90.736 12.787 5
    PIAF6.745 27.882 00.051 30.387 50.990 93.839 4
    FAGF6.830 57.183 10.063 90.409 20.789 24.108 7
    Img3WLS5.319 35.275 60.029 80.363 60.577 32.184 9
    GF6.439 07.655 10.012 30.345 00.564 41.086 6
    VGG4.888 85.075 90.015 30.356 50.440 61.157 7
    RES5.021 25.131 10.024 30.402 60.485 31.767 4
    PIAF5.747 07.900 90.018 80.362 70.729 01.408 6
    FAGF6.818 16.604 10.030 80.404 10.903 42.812 8
    Img4WLS6.849 99.366 20.057 70.397 00.847 94.387 9
    GF6.480 28.688 30.048 70.434 40.625 53.422 7
    VGG6.205 19.429 10.030 00.387 30.607 72.175 2
    RES6.367 59.537 30.049 30.424 60.639 23.485 9
    PIAF6.824 98.482 30.057 00.419 70.773 54.242 4
    FAGF7.186 39.805 60.094 10.459 51.088 67.191 4
    Img5WLS6.315 27.754 20.040 80.379 50.994 63.852 7
    GF6.020 58.634 90.020 40.434 50.663 52.172 7
    VGG5.904 57.547 30.019 60.403 40.742 61.899 1
    RES5.979 07.560 00.030 60.429 20.800 32.843 4
    PIAF6.304 68.097 40.024 60.412 71.156 02.617 2
    FAGF6.554 78.496 40.050 20.427 11.228 25.467 9
    Img6WLS6.609 78.354 90.025 80.297 10.929 62.585 7
    GF5.856 47.114 00.017 30.331 30.643 51.721 4
    VGG6.187 38.440 00.013 40.302 60.746 71.401 2
    RES6.256 78.441 40.019 30.334 90.783 61.952 8
    PIAF6.663 58.436 00.026 10.334 90.976 62.497 5
    FAGF6.711 38.622 60.041 50.380 01.135 94.308 0
    Table 2. Comparison of objective evaluation indicators
    Yanchun YANG, Yongping LI, Jianwu DANG, Yangping WANG. Infrared and visible image fusion based on fast alternating guided filtering and CNN[J]. Optics and Precision Engineering, 2023, 31(10): 1548
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