Acta Photonica Sinica, Volume. 49, Issue 10, 1010001(2020)
Remote Sensing Image Fusion Based on Spectral Response Function and Global Variance Matching
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Fig. 3. Panchromatic, multispectral and fusion images of GF-2 PMS1 (false color composite)
Fig. 4. Panchromatic, multispectral and fusion images of SV1-03 satellite (true color composite)
Table 1. The weight coefficients of each band in multispectral simulation panchromatic of GF-2 and SV1 satellite
View tableView in ArticleTable 1. The weight coefficients of each band in multispectral simulation panchromatic of GF-2 and SV1 satellite
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 2. Comparison of quantitative indexes of different fusion images
View tableView in ArticleTable 2. Comparison of quantitative indexes of different fusion images
Method GF2(0.8 m) SV1(0.5 m) p =1)q =1)QNR( p =1)q =1)QNR( 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
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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
Paper Information
Category: Image Processing
Received: Jun. 30, 2020
Accepted: Aug. 19, 2020
Published Online: Mar. 10, 2021
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