Version 1
: Received: 27 September 2020 / Approved: 28 September 2020 / Online: 28 September 2020 (11:05:51 CEST)
How to cite:
Farhadi, M.; Hoshyarmanesh, H. Comparison of Image Fusion Techniques Using Worldview-3 Data. Preprints2020, 2020090685. https://doi.org/10.20944/preprints202009.0685.v1
Farhadi, M.; Hoshyarmanesh, H. Comparison of Image Fusion Techniques Using Worldview-3 Data. Preprints 2020, 2020090685. https://doi.org/10.20944/preprints202009.0685.v1
Farhadi, M.; Hoshyarmanesh, H. Comparison of Image Fusion Techniques Using Worldview-3 Data. Preprints2020, 2020090685. https://doi.org/10.20944/preprints202009.0685.v1
APA Style
Farhadi, M., & Hoshyarmanesh, H. (2020). Comparison of Image Fusion Techniques Using Worldview-3 Data. Preprints. https://doi.org/10.20944/preprints202009.0685.v1
Chicago/Turabian Style
Farhadi, M. and Hossein Hoshyarmanesh. 2020 "Comparison of Image Fusion Techniques Using Worldview-3 Data" Preprints. https://doi.org/10.20944/preprints202009.0685.v1
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.
Keywords
fusion; pansharpening; image quality; Worldview-3; quality index
Subject
Environmental and Earth Sciences, Environmental Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
