Hyperspectral image fusion method based on second generation wavelet

被引：0
|
作者：
Wang, Kecheng [1 ]
Yang, Jie [1 ]
Hou, Zhefei [1 ]
Liu, Yu [1 ]
机构：
[1] Wuhan Univ Technol, Sch Informat Engn, Wuhan 430063, Peoples R China
来源：
REMOTE SENSING AND GIS DATA PROCESSING AND APPLICATIONS; AND INNOVATIVE MULTISPECTRAL TECHNOLOGY AND APPLICATIONS, PTS 1 AND 2 | 2007年 / 6790卷
关键词：
hyperspectral image; image fusion; second generation wavelet; variance weighting; Neville filters;
D O I：
10.1117/12.750426
中图分类号：
TP7 [遥感技术];
学科分类号：
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要：
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.
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页数：8
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