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- W3091632718 abstract "Image fusion is a useful tool for producing a high-resolution multispectral image to be used for land use and land cover mapping. In this study, we use nine pansharpening algorithms namely Color Normalized (CN), Gram-Schmidt (GS), Hyperspherical Color Space (HCS), High Pass Filter (HPF), Nearest-Neighbor Diffusion (NND), Principal Component Analysis (PCA), Resolution Merge (RM), Stationary Wavelet Transform (SWT), and Wavelet Resolution Merge (WRM) to fusion Worldview-3 multispectral Bands and panchromatic band. In spectral and spatial fidelity, several image quality metrics are used to evaluate the performance of pansharpening algorithms. The SWT and PCA algorithms showed better results compared to other pansharpening algorithms while GS and CN algorithms showed the worst results for the original image fusion. The effect of fusion on each band was separately investigated and according to the calculations, we found that the CoastalBlue band and the Blue band showed the best result and the NIR-1 band and NIR-2 band show the worst result for the original image fusion. In the end, we conclude that the choice of fusion method depends on the requirement of remote sensing application." @default.
- W3091632718 created "2020-10-08" @default.
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- W3091632718 creator A5088047373 @default.
- W3091632718 date "2020-09-28" @default.
- W3091632718 modified "2023-10-14" @default.
- W3091632718 title "Comparison of Image Fusion Techniques Using Worldview-3 Data" @default.
- W3091632718 doi "https://doi.org/10.20944/preprints202009.0685.v1" @default.
- W3091632718 hasPublicationYear "2020" @default.
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