Remote Sensing Image Fusion Based on Particle Swarm Optimization and Adaptive Injection Model

Shize Li; Yan Dong

doi:10.3788/LOP231414

Laser & Optoelectronics Progress, Volume. 61, Issue 8, 0828002(2024)

Remote Sensing Image Fusion Based on Particle Swarm Optimization and Adaptive Injection Model

Shize Li and Yan Dong^*

Author Affiliations

Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, Yunnan, China

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Abstract Get PDF(in Chinese)

Figures & Tables(12)

Fig. 1. Flow chart of fusion method

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Fig. 2. Correspondence of bilinear interpolation algorithm

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Fig. 3. WorldView-2 experimental images. (a) MS; (b) PAN

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Fig. 4. WorldView-2 image fusion results. (a) BT; (b) DGIF; (c) NSCT; (d) DTCWT; (e) PCA; (f) proposed method

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Fig. 5. GF-2 experimental images. (a) MS; (b) PAN

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Fig. 6. GF-2 image fusion results. (a) BT; (b) DGIF; (c) NSCT; (d) DTCWT; (e) PCA; (f) proposed method

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Fig. 7. GeoEye experimental images. (a) MS; (b) PAN

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Fig. 8. GeoEye image fusion results. (a) BT; (b) DGIF; (c) NSCT; (d) DTCWT; (e) PCA; (f) proposed method

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Table 1. Initial parameter settings for PSO
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Table 1. Initial parameter settings for PSO
PSO setting parameter Number
Number of particles 20.00
Population learning factor 2.10
Personal learning factor 2.10
Initial inertial weight 0.90
Final inertial weight 0.40
Number of iterations 200

Table 2. Quantitative evaluation of WorldView-2 image fusion results

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Table 2. Quantitative evaluation of WorldView-2 image fusion results

Image	Method	AG↑	SF↑	EI↑	E↑	Q^AB/F↑	CE↓
1	BT	5.201	14.916	55.273	6.722	0.416	0.447
	DGIF	6.462	18.419	67.220	7.081	0.404	0.109
	NSCT	6.395	18.571	66.390	6.895	0.495	0.119
	DTCWT	6.336	17.036	67.351	7.062	0.421	0.118
	PCA	6.362	17.917	67.264	6.959	0.504	0.348
	Proposed	6.682	19.501	69.160	6.930	0.445	0.101
2	BT	4.795	14.508	50.566	6.780	0.454	0.457
	DGIF	5.048	16.497	55.037	7.002	0.468	0.307
	NSCT	5.401	16.009	54.139	6.798	0.529	0.311
	DTCWT	5.094	14.450	53.693	7.089	0.462	0.336
	PCA	5.112	14.806	53.627	7.024	0.523	0.364
	Proposed	5.559	17.603	57.039	6.998	0.477	0.293

Table 3. Quantitative evaluation of GF-2 image fusion results

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Table 3. Quantitative evaluation of GF-2 image fusion results

Image	Method	AG↑	SF↑	EI↑	E↑	Q^AB/F↑	CE↓
1	BT	12.241	30.183	112.560	7.540	0.351	0.333
	DGIF	12.654	31.035	111.973	7.553	0.421	0.193
	NSCT	11.209	25.324	79.413	7.556	0.379	0.200
	DTCWT	8.388	21.553	85.083	7.565	0.417	0.170
	PCA	12.566	30.258	112.640	7.564	0.374	0.181
	Proposed	11.367	31.334	112.770	7.571	0.407	0.167
2	BT	13.479	32.222	121.590	7.704	0.222	0.528
	DGIF	12.191	32.389	111.039	7.691	0.460	0.408
	NSCT	11.059	27.601	95.451	7.709	0.479	0.337
	DTCWT	9.680	24.762	101.740	7.739	0.468	0.320
	PCA	13.022	32.542	124.550	7.706	0.449	0.327
	Proposed	12.295	32.808	127.210	7.722	0.476	0.280

Table 4. Quantitative evaluation of GeoEye image fusion results

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Table 4. Quantitative evaluation of GeoEye image fusion results

Image	Method	AG↑	SF↑	EI↑	E↑	Q^AB/F↑	CE↓
1	BT	5.210	13.840	55.475	7.082	0.255	0.799
	DGIF	6.391	20.804	77.300	7.291	0.551	0.219
	NSCT	6.696	20.819	77.267	7.283	0.504	0.237
	DTCWT	6.201	16.609	66.077	7.268	0.486	0.229
	PCA	7.415	20.771	78.049	7.198	0.503	0.229
	Proposed	7.599	20.850	78.056	7.335	0.542	0.211
2	BT	5.402	13.699	58.044	7.260	0.296	0.388
	DGIF	5.770	16.519	65.391	7.530	0.511	0.311
	NSCT	5.681	16.539	63.058	7.351	0.503	0.339
	DTCWT	5.671	14.232	61.036	7.510	0.496	0.228
	PCA	5.824	16.104	67.602	7.515	0.540	0.245
	Proposed	6.080	16.705	64.905	7.545	0.545	0.299

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Shize Li, Yan Dong. Remote Sensing Image Fusion Based on Particle Swarm Optimization and Adaptive Injection Model[J]. Laser & Optoelectronics Progress, 2024, 61(8): 0828002

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