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植被信息提取過(guò)程中ETM+遙感影像融合和分類(lèi)試驗(yàn)
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    摘要:

    利用HIS,、PCA,、Brovey及小波變換4種圖像融合方法對(duì)南京地區(qū)植被信息提取過(guò)程中ETM+遙感影像進(jìn)行融合和分類(lèi)試驗(yàn),。從信息量,、高分辨率信息的融入度和分類(lèi)精度三方面,，對(duì)融合圖像進(jìn)行光譜質(zhì)量和空間結(jié)構(gòu)信息的定量評(píng)價(jià),。試驗(yàn)結(jié)果表明，Brovey變換更適合植被信息提取時(shí)的ETM+圖像融合,，并能夠較明顯提高影像的分類(lèi)精度,。

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    Remote sensing image fusion is an effective method in farm target identification. The purpose of this study is to investigate the optimum method of remote sensing image fusion for the vegetation information extraction of Nanjing. First, the HIS, PCA, Brovey and the wavelet transforms were applied to the merger of ETM+ PAN and the ETM+ multi-spectrum remote sensing image. Then the merged images were quantitatively evaluated according to their standard spectrum quality and spatial structure information based on the information content evaluation, the high resolution information integrate and the classified precision. The experimental results showed that the Brovey transforms is more effective than the other algorithms and could significantly improve the classification accuracy of the fused imagery in the exaction of vegetation information of Nanjing.

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沈明霞,何瑞銀,叢靜華.植被信息提取過(guò)程中ETM+遙感影像融合和分類(lèi)試驗(yàn)[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2007,38(8):109-112.[J]. Transactions of the Chinese Society for Agricultural Machinery,2007,38(8):109-112.

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