Remote Sensing Image Fusion Based on Spectral Response Function and Global Variance Matching

Jun-jie LI; Qiao-yang FU; Tao JIANG

doi:10.3788/gzxb20204910.1010001

Journals >Acta Photonica Sinica >Volume 49 >Issue 10 >Page 1010001 > Article

Acta Photonica Sinica
Vol. 49, Issue 10, 1010001 (2020)

Remote Sensing Image Fusion Based on Spectral Response Function and Global Variance Matching

Jun-jie LI, Qiao-yang FU, and Tao JIANG

Author Affiliations

China Centre for Resources Satellite Data and Application，Beijing 100094，China

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DOI: 10.3788/gzxb20204910.1010001 Cite this Article

Jun-jie LI, Qiao-yang FU, Tao JIANG. Remote Sensing Image Fusion Based on Spectral Response Function and Global Variance Matching[J]. Acta Photonica Sinica, 2020, 49(10): 1010001 Copy Citation Text

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Fig. 1. Flow chart of proposed remote sensing image fusion method

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Fig. 2. Spectral response function of GF-2 PMS1 sensor bands

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Fig. 3. Panchromatic, multispectral and fusion images of GF-2 PMS1 (false color composite)

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Fig. 4. Panchromatic, multispectral and fusion images of SV1-03 satellite (true color composite)

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Fig. 5. Spatial profile of GF-2 PMS1 sample image

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Sensor name	Band1(blue)	Band2(green)	Band3(red)	Band4(NIR)
GF-2 PMS1	0.144 8	0.185 2	0.294 5	0.375 5
GF-2 PMS2	0.141 8	0.181 7	0.299 8	0.376 7
SV1-01	0.140 1	0.182 4	0.303 6	0.373 9
SV1-02	0.133 4	0.169 3	0.294 3	0.403 0
SV1-03	0.128 9	0.163 1	0.312 6	0.395 4
SV1-04	0.127 0	0.166 5	0.314 0	0.392 6

Table 1. The weight coefficients of each band in multispectral simulation panchromatic of GF-2 and SV1 satellite

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Method	GF2(0.8 m)			SV1(0.5 m)
Method	$D_{λ}$ (p=1)	$D_{s}$ (q=1)	QNR( $α = β = 1$ )	$D_{λ}$ (p=1)	$D_{s}$ (q=1)	QNR( $α = β = 1$ )
GS	0.026 9	0.049 3	0.925 2	0.051 2	0.161 7	0.790 3
HPF	0.044 5	0.076 8	0.882 1	0.064 5	0.166 9	0.779 3
SRF⁃VAR	0.022 0	0.033 8	0.944 9	0.053 7	0.147 2	0.807 0
PCA	0.036 6	0.256 4	0.716 4	0.101 2	0.228 5	0.693 4

Table 2. Comparison of quantitative indexes of different fusion images

Jun-jie LI, Qiao-yang FU, Tao JIANG. Remote Sensing Image Fusion Based on Spectral Response Function and Global Variance Matching[J]. Acta Photonica Sinica, 2020, 49(10): 1010001

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