Pansharpening Based on Multi-Branch CNN

Hongbin Wang; Song Xiao; Jiahui Qu; Wenqian Dong; Tongzhen Zhang

doi:10.3788/AOS202141.0710001

Journals >Acta Optica Sinica >Volume 41 >Issue 7 >Page 0710001 > Article

Acta Optica Sinica
Vol. 41, Issue 7, 0710001 (2021)

Pansharpening Based on Multi-Branch CNN

Hongbin Wang, Song Xiao^**, Jiahui Qu^*, Wenqian Dong, and Tongzhen Zhang

Author Affiliations

State Key Laboratory of Integrated Services Networks, Xidian University, Xi′an, Shaanxi 710071, China

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DOI: 10.3788/AOS202141.0710001 Cite this Article Set citation alerts

Hongbin Wang, Song Xiao, Jiahui Qu, Wenqian Dong, Tongzhen Zhang. Pansharpening Based on Multi-Branch CNN[J]. Acta Optica Sinica, 2021, 41(7): 0710001 Copy Citation Text

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Fig. 1. Network structure in proposed algorithm

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Fusion results of 40th image in Pavia Center dataset by different algorithms. (a) Reference image; (b) proposed algorithm; (c) SFIM; (d) MTF-GLP-HPM; (e) Bayesian sparse; (f) GSA; (g) PCA; (h) CNMF

Fig. 2. Fusion results of 40th image in Pavia Center dataset by different algorithms. (a) Reference image; (b) proposed algorithm; (c) SFIM; (d) MTF-GLP-HPM; (e) Bayesian sparse; (f) GSA; (g) PCA; (h) CNMF

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Fig. 3. Fusion results of 24th image in Pavia Center dataset by different algorithms. (a) Reference image; (b) proposed algorithm; (c) SFIM; (d) MTF-GLP-HPM; (e) Bayesian sparse; (f) GSA; (g) PCA; (h) CNMF

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Fig. 4. Fusion results of 24th image in CAVE dataset by different algorithms. (a) Reference image; (b) proposed algorithm; (c) SFIM; (d) MTF-GLP-HPM; (e) Bayesian sparse; (f) GSA; (g) PCA; (h) CNMF

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Fig. 5. Fusion results of 5th image in CAVE dataset by different algorithms. (a) Reference image; (b) proposed algorithm; (c) SFIM; (d) MTF-GLP-HPM; (e) Bayesian sparse; (f) GSA; (g) PCA; (h) CNMF

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Parameter	Bayesiansparse	CNMF	GSA	MTF-GLP-HPM	PCA	SFIM	Proposedalgorithm
CC	0.9337	0.9251	0.9448	0.9675	0.9145	0.9631	0.9791
SAM	8.3296	7.1236	7.4254	6.2297	7.6162	6.2508	4.9153
RMSE	0.0363	0.0385	0.0317	0.0250	0.0370	0.0267	0.0185
ERGAS	5.7224	5.7865	4.9169	3.6290	5.7443	4.0159	2.8287

Table 1. Evaluation results on Pavia Center dataset

Parameter	Bayesiansparse	CNMF	GSA	MTF-GLP-HPM	PCA	SFIM	Proposedalgorithm
CC	0.9942	0.9925	0.9936	0.9884	0.9893	0.9895	0.9968
SAM	5.5619	6.6133	5.8892	6.5877	6.5012	6.1081	4.4402
RMSE	0.0140	0.0168	0.0163	0.0199	0.0230	0.0193	0.0123
ERGAS	3.6471	3.9827	3.8574	5.3817	4.1675	5.0852	2.6174

Table 2. Evaluation results on CAVE dataset

Hongbin Wang, Song Xiao, Jiahui Qu, Wenqian Dong, Tongzhen Zhang. Pansharpening Based on Multi-Branch CNN[J]. Acta Optica Sinica, 2021, 41(7): 0710001

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