10 January 2005 Comparison of pixel-based fusion between multispectral data and high spatial resolution data
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Abstract
In the paper, experiments and analysis of three pixel-based fusion methods had been discussed. The fusion methods include IHS, PCA and Brovey transform method. The fusion experiments were carried out in two circs, that is, between Landsat TM multi-spectral data and SPOT-4 Pan data, Landsat TM multi-spectral data and IRS-C Pan data. From the fusion results, the definition of all fusion images were improved greatly compared to the Landsat TM image. Especially the linear ground objects are much clear, such as the roads, the residents, the bridges, etc. According to the fusion between Landsat TM data and SPOT-4 Pan data, the Brovey fusion method was the best one. The PCA fusion method was better than the IHS fusion method. According to the fusion between Landsat TM data and IRS-C Pan data, the Brovey fusion method was also the best one. But the IHS fusion method was better than the PCA fusion method. Maximum likelihood method of classification was carried out on the fusion result, and classification accuracy of the classification results were evaluated. From the evaluation result, it can be concluded that classification accuracy of the Brovey fusion result is the highest between Landsat TM data and IRS-C Pan data. Classification accuracy of the IHS fusion result is the highest between Landsat TM data and SPOT-4 Pan data.
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Shuhe Zhao, Shuhe Zhao, Ziyu Wang, Ziyu Wang, Xieqiong Dong, Xieqiong Dong, Xiuwan Chen, Xiuwan Chen, } "Comparison of pixel-based fusion between multispectral data and high spatial resolution data", Proc. SPIE 5657, Image Processing and Pattern Recognition in Remote Sensing II, (10 January 2005); doi: 10.1117/12.578689; https://doi.org/10.1117/12.578689
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