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Proceedings Paper

Comparison of pixel-based fusion between multispectral data and high spatial resolution data
Author(s): Shuhe Zhao; Ziyu Wang; Xieqiong Dong; Xiuwan Chen
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Paper 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.

Paper Details

Date Published: 10 January 2005
PDF: 8 pages
Proc. SPIE 5657, Image Processing and Pattern Recognition in Remote Sensing II, (10 January 2005); doi: 10.1117/12.578689
Show Author Affiliations
Shuhe Zhao, Peking Univ. (China)
Ziyu Wang, Peking Univ. (China)
Xieqiong Dong, Nanjing Univ. (China)
Ctr. for Agrometeorology and Remote Sensing Application of Yunnan (China)
Xiuwan Chen, Peking Univ. (China)


Published in SPIE Proceedings Vol. 5657:
Image Processing and Pattern Recognition in Remote Sensing II
Yoshifumi Yasuoka; Stephen G. Ungar, Editor(s)

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