Infrared Mid-Wave and Long-Wave Image Fusion Based on FABEMD and Improved Local Energy Window

Xiao-rong CUI; Tao SHEN; Jian-lu HUANG; Bin-bin SUN

doi:10.3964/j.issn.1000-0593(2021)07-2043-07

Journals >Spectroscopy and Spectral Analysis >Volume 41 >Issue 7 >Page 2043 > Article

Spectroscopy and Spectral Analysis
Vol. 41, Issue 7, 2043 (2021)

Infrared Mid-Wave and Long-Wave Image Fusion Based on FABEMD and Improved Local Energy Window

Xiao-rong CUI^*, Tao SHEN^*;, Jian-lu HUANG, and Bin-bin SUN

Author Affiliations

Rocket Force University of Engineering, Xi'an 710025, China

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DOI: 10.3964/j.issn.1000-0593(2021)07-2043-07 Cite this Article

Xiao-rong CUI, Tao SHEN, Jian-lu HUANG, Bin-bin SUN. Infrared Mid-Wave and Long-Wave Image Fusion Based on FABEMD and Improved Local Energy Window[J]. Spectroscopy and Spectral Analysis, 2021, 41(7): 2043 Copy Citation Text

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Fig. 1. Infrared mid-wave and long-wave image fusion scheme based on FABEMD

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Fig. 2. Comparison of symmetrical surrounding areas based on MSS

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Fig. 3. Original MWIR image detection results of different saliency algorithms

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Fig. 4. Chimney fusion image

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Fig. 5. Building fusion image

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Fig. 6. Roof fusion image

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Fig. 7. Tank fusion image

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融合结果	评价因子
融合结果	AG	SF	NMI	SSIM	Q^AB/F	EN
图4(c)	1.981 7	4.803 2	0.503 1	0.664 5	0.630 1	7.130 7
图4(d)	2.492 6	14.707 5	0.500 9	0.687 7	0.647 9	7.283 2
图4(e)	2.473 9	14.686 4	0.506 2	0.688 4	0.644 4	7.252 9
图4(f)	2.471 4	6.014 8	0.471 8	0.705 9	0.633 8	6.966 3
图4(g)	2.036 4	4.819 6	0.510 1	0.653 5	0.595 2	7.240 2
图4(h)	2.374 6	14.177 4	0.520 7	0.618 0	0.565 8	6.797 9
图4(i)	2.052 5	5.135 7	0.541 4	0.644 5	0.553 9	7.562 3
图4(j)	2.061 0	5.631 4	0.553 6	0.608 1	0.543 6	7.289 0
图5(c)	4.838 9	9.503 3	0.229 7	0.549 1	0.513 6	6.853 5
图5(d)	4.513 5	8.909 8	0.237 3	0.554 2	0.512 1	6.909 7
图5(e)	4.550 2	8.968 8	0.236 8	0.555 4	0.509 5	6.901 0
图5(f)	4.707 0	9.176 7	0.211 4	0.556 3	0.520 2	6.701 9
图5(g)	5.012 2	9.549 0	0.158 8	0.505 3	0.463 6	6.580 4
图5(h)	4.566 6	8.728 3	0.281 9	0.534 4	0.488 4	6.741 9
图5(i)	4.889 5	9.196 9	0.235 0	0.534 8	0.468 1	6.385 3
图5(j)	5.172 7	9.970 7	0.225 4	0.507 1	0.470 1	6.972 0
图6(c)	1.980 9	5.388 2	0.461 6	0.579 0	0.599 6	7.308 2
图6(d)	1.825 0	6.286 4	0.467 1	0.609 4	0.604 8	7.307 1
图6(e)	1.849 4	4.461 5	0.466 6	0.608 8	0.602 3	7.307 2
图6(f)	1.774 5	4.838 1	0.434 0	0.580 8	0.554 9	7.010 9
图6(g)	2.097 2	5.631 3	0.440 2	0.542 3	0.499 3	7.234 8
图6(h)	1.709 5	6.010 3	0.462 3	0.569 4	0.528 2	7.071 4
图6(i)	1.825 2	4.696 6	0.410 3	0.505 5	0.511 6	7.173 4
图6(j)	1.699 7	6.321 7	0.467 8	0.589 7	0.524 5	7.226 7
图7(c)	1.895 3	5.288 0	0.412 0	0.636 7	0.582 7	7.206 9
图7(d)	1.987 1	5.301 1	0.417 1	0.654 8	0.576 1	7.209 0
图7(e)	2.010 9	5.331 3	0.416 8	0.655 3	0.575 6	7.208 4
图7(f)	2.294 3	4.869 7	0.396 1	0.639 8	0.561 9	7.158 5
图7(g)	2.156 5	5.093 4	0.404 1	0.593 1	0.502 9	6.871 3
图7(h)	1.883 1	5.322 8	0.469 1	0.613 3	0.501 4	6.662 5
图7(i)	2.079 8	4.939 2	0.384 1	0.584 2	0.493 4	7.072 7
图7(j)	2.174 2	5.496 9	0.438 7	0.618 8	0.500 4	6.798 2

Table 1. Objective evaluation results of indicators 1—6

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