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Proceedings Paper

Comparative analysis of fusion models based on remote sensing applications
Author(s): Ying Zhang; Binbin He; Xiaowen Li
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Paper Abstract

The evaluation of performances of fusion methods is a key problem in remote sensing image fusion. In this paper, four representative fusion methods, PCA fusion, WT fusion, CT fusion and TLS-GIF-WC, are adopted to fuse two sets of ALI images for comparison. The fusion products are applied to two remote sensing applications, vegetation index extraction and image classification. The normalized difference vegetation index (NDVI), vegetation coverage and classification accuracy indices are adopted to compare the fusion products. Experiments show that the GIF fusion products are more adaptive for vegetation application, since the NDVI and vegetation coverage extracted from the fusion product are consistent with that extracted from the initial image, and the ARSIS concept fusion and TLS-GIF-WC products are more adaptive for image classification, because of the higher classification accuracy.

Paper Details

Date Published: 30 October 2009
PDF: 7 pages
Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74982X (30 October 2009); doi: 10.1117/12.832813
Show Author Affiliations
Ying Zhang, Univ. of Electronic Science and Technology of China (China)
Binbin He, Univ. of Electronic Science and Technology of China (China)
Xiaowen Li, Univ. of Electronic Science and Technology of China (China)


Published in SPIE Proceedings Vol. 7498:
MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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