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基于主成分分析與Brovey變換的ETM+影像植被信息提取
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    在ETM+影像全色波段和多光譜數(shù)據(jù)融合時(shí),Brovey變換是一種較好的融合方法,但是Brovey變換所利用的波段信息量少,并且在對融合后影像分類時(shí)常將存在陰影的植被覆蓋區(qū)誤判為水體。因此將主成分和歸一化植被指數(shù)(NDVI)作為Brovey變換融合時(shí)的波段,實(shí)驗(yàn)結(jié)果顯示融合后的影像更利于后期植被信息提取。

    Abstract:

    Data fusion on remote sensing images can improve visualization of the images involved. For the data fusion between multi-spectral images and panchromatic image of Landsat7 satellite, Brovey transform is better than PCA transformation or HIS transformation. However, Brovey transformation only uses three bands of multi-spectral images. PCA can compress more than 95% of the original information into PC1 and PC2, and the information of vegetation can be showed in NDVI image. So, PC1,PC2 and NDVI were used as the fusion bands of Brovey transformation in this paper. The experimental results showed that vegetation information can be better obtained by the bands compounding than by former bands compounding.

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沈明霞,何瑞銀,叢靜華,楊俊.基于主成分分析與Brovey變換的ETM+影像植被信息提取[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2007,38(9):87-89.[J]. Transactions of the Chinese Society for Agricultural Machinery,2007,38(9):87-89.

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