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Proceedings Paper

Hyperspectral image fusion method based on second generation wavelet
Author(s): Kecheng Wang; Jie Yang
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Paper Abstract

A hyperspectral image fusion method based on second generation wavelet with variance weighting is proposed in this paper. This method includes three major steps: Firstly, decompose the original 220 bands image by second generation wavelet transform, namely predict and update sub-images on rectangle and quincunx grids by Neville filters. Secondly, use variance as fusion weight to multiply decomposed coefficients. Finally the fused image was reconstructed by reverse second generation wavelet transform. AVIRIS hyperspectral image was selected in the experiments, the results of which illustrated that the method based on second generation wavelet can utilize both spatial and spectral characteristics of source images more adequately. This novel method improved qualitative and quantitative results, compared to previous wavelet fusion methods. Therefore, the effect of variance weighting fusion is superior to that of averaging fusion.

Paper Details

Date Published: 14 November 2007
PDF: 8 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 679027 (14 November 2007); doi: 10.1117/12.750426
Show Author Affiliations
Kecheng Wang, Wuhan Univ. of Technology (China)
Jie Yang, Wuhan Univ. of Technology (China)


Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications

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