Image Fusion Based on Improved Region Growing and Guided Filtering

Jiamin Gong; Shanghui Liu; Ku Jin; Haiyang Liu; Xumeng Wei

doi:10.3788/LOP222347

Journals >Laser & Optoelectronics Progress >Volume 60 >Issue 16 >Page 1610009 > Article

Laser & Optoelectronics Progress
Vol. 60, Issue 16, 1610009 (2023)

Image Fusion Based on Improved Region Growing and Guided Filtering

Jiamin Gong¹, Shanghui Liu^2、*, Ku Jin², Haiyang Liu², and Xumeng Wei²

Author Affiliations

¹School of Modern Post, Xi'an University of Posts and Telecommunications, Xi'an 710061, Shaanxi, China

²School of Communication and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, Shaanxi, China

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DOI: 10.3788/LOP222347 Cite this Article Set citation alerts

Jiamin Gong, Shanghui Liu, Ku Jin, Haiyang Liu, Xumeng Wei. Image Fusion Based on Improved Region Growing and Guided Filtering[J]. Laser & Optoelectronics Progress, 2023, 60(16): 1610009 Copy Citation Text

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Infrared target extraction based on IRG. (a) Infrared image 1; (b) infrared image 2; (c) infrared image 3; (d) extraction target of image 1; (e) extraction target of image 2; (f) extraction target of image 3

Fig. 1. Infrared target extraction based on IRG. (a) Infrared image 1; (b) infrared image 2; (c) infrared image 3; (d) extraction target of image 1; (e) extraction target of image 2; (f) extraction target of image 3

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Fig. 2. DCSCM

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Fig. 3. Flow chart of proposed fusion method

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Fig. 4. Three groups of visible and infrared images. (a) Visible image of group 1; (b) visible image of group 2; (c) visible image of group 3; (d) infrared image of group 1; (e) infrared image of group 2; (f) infrared image of group 3

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Fig. 5. Group 1 images and fusion results. (a) MGFF algorithm; (b) RGFFT algorithm; (c) MST algorithm; (d) VIP algorithm; (e) SCMGF algorithm; (f) proposed algorithm

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Fig. 6. Group 2 images and fusion results. (a) MGFF algorithm; (b) RGFFT algorithm; (c) MST algorithm; (d) VIP algorithm; (e) SCMGF algorithm; (f) proposed algorithm

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Fig. 7. Group 3 images and fusion results. (a) MGFF algorithm; (b) RGFFT algorithm; (c) MST algorithm; (d) VIP algorithm; (e) SCMGF algorithm; (f) proposed algorithm

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Group	Algorithm	STD	MI	AG	EN	Q^AB/F	SSIM
Group 1	MGFF	31.8944	1.8872	4.4707	6.5396	0.5653	0.4394
	RGFFT	35.8214	3.3694	4.5047	6.7683	0.5753	0.4747
	MST	29.7569	2.6295	4.1413	6.2525	0.5575	0.4219
	VIP	38.2701	0.2657	4.1800	6.6984	0.6072	0.6623
	SCMGF	35.1244	2.7851	4.2004	6.7825	0.5175	0.4054
	Proposed algorithm	39.0254	3.5856	4.5786	6.8613	0.6153	0.4726
Group 2	MGFF	36.6809	1.7426	4.5351	6.8599	0.4702	0.5268
	RGFFT	58.8457	3.1581	4.6010	7.3429	0.4729	0.4307
	MST	52.1024	3.0416	4.3414	6.8654	0.4563	0.4920
	VIP	52.8195	0.3818	4.3009	6.9521	0.5332	0.7334
	SCMGF	59.9936	3.3897	4.2536	7.3499	0.4118	0.4496
	Proposed algorithm	63.1001	3.2352	4.7744	7.4096	0.5391	0.4598
Group 3	MGFF	31.5410	0.3571	5.6886	6.8607	0.1420	0.1299
	RGFFT	45.9761	2.3598	5.2517	6.9519	0.4546	0.4904
	MST	54.6009	4.2285	5.3389	6.7975	0.5562	0.4873
	VIP	44.2157	0.0872	4.3456	6.5474	0.4596	0.7206
	SCMGF	36.4719	1.8304	5.6384	7.1768	0.4375	0.4795
	Proposed algorithm	46.5446	2.4722	5.8432	6.9413	0.4780	0.4989

Table 1. Three groups of objective evaluation indicators of fused images

Jiamin Gong, Shanghui Liu, Ku Jin, Haiyang Liu, Xumeng Wei. Image Fusion Based on Improved Region Growing and Guided Filtering[J]. Laser & Optoelectronics Progress, 2023, 60(16): 1610009

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