X-ray image fusion for ancient bronze mirror based on intuitionistic fuzzy set entropy measure and salient feature detection

Property	Value
Equipment type	ART-GIL350/6 fixed flaw detector
Operating voltage range	95-350 KV
IP board model	HD-IP Plus 18×24 cm
Image pixel size	50 μm
High energy tube voltage	250 kV
Low energy tube voltage	180 kV
Tube current	5 mA
Exposure time	120 s

Table 2. 不同参数和下的客观评价结果

View table

View in Article

Table 2. 不同参数和下的客观评价结果

Metrics		$σ_{s}$ =1.6	$σ_{s}$ =1.7	$σ_{s}$ =1.8
	$σ_{r}$ =0.07	4.774 6	4.780 5	4.779 5
AG	$σ_{r}$ =0.09	4.776 2	4.782 2	4.781 0
	$σ_{r}$ =0.1	4.774 8	4.781 0	4.780 3
	$σ_{r}$ =0.07	18.982 1	19.012 3	18.989 1
SF	$σ_{r}$ =0.09	18.984 1	19.015 9	18.993 4
	$σ_{r}$ =0.1	18.983 0	19.013 7	18.990 2
	$σ_{r}$ =0.07	83.383 6	83.389 9	83.387 5
SD	$σ_{r}$ =0.09	83.386 7	83.392 6	83.389 6
	$σ_{r}$ =0.1	83.384 5	83.390 2	83.388 0
	$σ_{r}$ =0.07	1.060 9	1.065 6	1.066 3
SCD	$σ_{r}$ =0.09	1.062 8	1.067 2	1.068 0
	$σ_{r}$ =0.1	1.060 5	1.065 8	1.066 8
	$σ_{r}$ =0.07	0.016 8	0.014 6	0.014 4
$N^{A B / F}$	$σ_{r}$ =0.09	0.015 8	0.013 9	0.013 6
	$σ_{r}$ =0.1	0.016 9	0.015 1	0.014 7
	$σ_{r}$ =0.07	0.745 5	0.750 4	0.749 2
SSIM	$σ_{r}$ =0.09	0.747 1	0.751 8	0.750 9
	$σ_{r}$ =0.1	0.746 0	0.751 2	0.749 8

Table 3. WAOL effectiveness analysis results

View table

View in Article

Table 3. WAOL effectiveness analysis results

Images	Operators	Metrics
Images	Operators	AG↑	SF↑	SD↑	SCD↑	$N^{A B / F}$ ↓	SSIM↑
Img1	MSF	6.050 3	20.166 3	78.619 0	1.038 7	0.011 0	0.761 5
Img1	SFE	6.071 1	20.197 2	78.623 9	1.046 3	0.010 6	0.762 2
Img2	MSF	3.056 2	13.901 4	93.379 0	1.136 2	0.014 7	0.756 0
Img2	SFE	3.059 4	13.910 3	93.392 1	1.138 8	0.014 5	0.756 8
Img3	MSF	4.251 4	18.302 3	81.112 1	0.940 1	0.011 5	0.805 5
Img3	SFE	4.258 4	18.326 4	81.122 0	0.944 3	0.011 3	0.805 3
Img4	MSF	4.123 2	15.035 5	77.927 6	1.061 5	0.007 6	0.773 7
Img4	SFE	4.135 1	15.061 8	77.940 7	1.067 8	0.007 5	0.773 2
Img5	MSF	6.378 3	27.592 2	85.888 7	1.134 8	0.026 1	0.661 7
Img5	SFE	6.386 9	27.583 7	85.884 5	1.138 7	0.025 6	0.661 7

Table 4. Comparison results of objective evaluation indicators

View table

View in Article

Table 4. Comparison results of objective evaluation indicators

Images	Methods	Metrics
Images	Methods	AG↑	SF↑	SD↑	SCD↑	$N^{A B / F}$ ↓	SSIM↑
Img1	CSMCA	4.452 9	14.658 3	57.684 1	0.602 8	0.017 8	0.689 7
	BM-PCNN	4.796 7	15.380 9	62.684 1	0.697 9	0.015 2	0.532 8
	JBF-LGE	5.147 9	17.004 1	78.391 8	1.163 8	0.013 3	0.756 3
	CBFM	5.041 9	16.016 3	64.406 0	0.562 1	0.010 8	0.455 3
	ETEM	5.140 5	17.165 7	78.046 7	1.064 0	0.013 3	0.746 7
	CrossFuse	5.027 1	16.872 9	77.986 3	0.974 8	0.017 0	0.750 9
	MFIF	4.639 8	15.072 3	61.762 8	0.713 1	0.011 1	0.670 6
	Ours	6.071 1	20.197 2	78.623 9	1.046 3	0.010 6	0.762 2

Table 4. Comparison results of objective evaluation indicators

View table

View in Article

Table 4. Comparison results of objective evaluation indicators

Images	Methods	Metrics
Images	Methods	AG↑	SF↑	SD↑	SCD↑	$N^{A B / F}$ ↓	SSIM↑
Img2	CSMCA	2.389 5	10.557 8	64.353 1	0.732 3	0.017 5	0.725 9
	BM-PCNN	2.549 4	11.433 5	74.428 4	0.556 4	0.017 4	0.572 3
	JBF-LGE	2.713 1	12.905 5	93.314 3	1.131 2	0.016 5	0.747 8
	CBFM	2.754 1	11.517 5	69.770 0	0.600 6	0.011 0	0.556 5
	ETEM	2.692 7	12.992 9	93.227 2	1.135 8	0.017 3	0.738 9
	CrossFuse	2.700 4	12.875 2	93.273 1	1.138 2	0.016 5	0.756 5
	MFIF	2.342 2	11.243 2	61.854 0	0.708 7	0.015 8	0.628 8
	Ours	3.059 4	13.910 3	93.392 1	1.138 8	0.014 5	0.756 8
Img3	CSMCA	3.027 2	13.300 3	65.354 5	0.603 5	0.018 0	0.763 7
	BM-PCNN	3.158 4	13.594 3	67.650 4	0.561 7	0.017 2	0.626 9
	JBF-LGE	3.404 3	14.537 5	80.867 8	0.966 8	0.014 9	0.798 2
	CBFM	3.231 1	13.487 7	62.452 5	0.667 0	0.013 6	0.506 4
	ETEM	3.391 0	15.076 3	80.746 4	0.962 0	0.015 0	0.770 7
	CrossFuse	3.262 7	14.742 9	80.022 9	0.773 2	0.017 5	0.802 1
	MFIF	3.100 8	12.829 0	67.673 7	0.525 1	0.012 5	0.768 3
	Ours	4.258 4	18.326 4	81.122 0	0.944 3	0.011 3	0.805 3
Img4	CSMCA	3.149 5	12.975 6	59.212 0	0.519 3	0.011 0	0.720 3
	BM-PCNN	3.434 5	13.636 6	67.167 1	0.539 8	0.009 4	0.491 5
	JBF-LGE	3.740 7	14.515 8	77.764 0	1.061 7	0.009 6	0.763 3
	CBFM	3.783 6	13.619 1	64.410 7	0.455 2	0.008 5	0.387 4
	ETEM	3.731 3	14.617 3	77.655 2	1.047 7	0.009 7	0.781 7
	CrossFuse	3.665 3	14.446 9	77.524 2	1.058 6	0.010 9	0.772 2
	MFIF	3.218 6	12.529 2	61.813 1	0.571 5	0.009 0	0.631 5
	Ours	4.135 1	15.061 8	77.940 7	1.067 8	0.007 5	0.773 2
Img5	CSMCA	4.765 8	19.635 1	67.298 8	0.784 0	0.027 7	0.606 7
	BM-PCNN	4.860 2	19.858 3	66.517 6	0.675 3	0.026 4	0.413 5
	JBF-LGE	5.310 2	22.586 0	85.560 5	1.105 2	0.028 7	0.647 1
	CBFM	5.739 1	21.534 5	70.225 3	0.641 1	0.022 4	0.340 0
	ETEM	5.304 6	23.230 6	85.362 0	1.060 8	0.032 0	0.658 2
	CrossFuse	5.011 3	22.417 7	85.524 2	1.284 9	0.033 6	0.659 3
	MFIF	4.880 4	20.340 0	69.771 8	0.795 2	0.026 1	0.524 6
	Ours	6.386 9	27.583 7	85.884 5	1.138 7	0.025 6	0.661 7

Table 5. Objective comparison of ablation experimental results

View table

View in Article

Table 5. Objective comparison of ablation experimental results

Methods	Metrics
Methods	AG↑	SF↑	SD↑	SCD↑	$N^{A B / F}$ ↓	SSIM↑
A B	4.637 5 4.631 4	18.579 9 18.566 8	82.843 9 83.045 6	0.986 4	0.016 0	0.656 8
A B	4.637 5 4.631 4	18.579 9 18.566 8	82.843 9 83.045 6	0.976 4	0.015 7	0.739 7
C	4.675 5	18.872 8	83.169 2	0.999 1	0.015 4	0.742 7
D	4.593 9	18.814 5	82.864 9	0.958 9	0.014 9	0.744 0
Ours	4.782 2	19.015 9	83.392 6	1.067 2	0.013 9	0.751 8

Table 6. Efficiency comparison results
View table
View in Article
Table 6. Efficiency comparison results
Methods Time/s Methods Time/s
CSMCA 56.27 ETEM 3.92
BM-PCNN 9.72 CrossFuse 6.73
JBF-LGE 1.01 MFIF 5.57
CBFM 8.05 Ours 2.12

Tools

Get Citation

Copy Citation Text

Meng WU, Qianwen ZHANG, Zengguo SUN, Jiankai XIANG, Ge GUO. X-ray image fusion for ancient bronze mirror based on intuitionistic fuzzy set entropy measure and salient feature detection[J]. Optics and Precision Engineering, 2025, 33(2): 262

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites