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植被信息提取过程中ETM+遥感影像融合和分类试验
引用本文:沈明霞,何瑞银,丛静华.植被信息提取过程中ETM+遥感影像融合和分类试验[J].农业机械学报,2007,38(8):109-112.
作者姓名:沈明霞  何瑞银  丛静华
作者单位:1. 南京农业大学工学院,210031,南京市
2. 南京森林公安专科学校,210042,南京市
基金项目:江苏省高技术研究发展计划项目
摘    要:利用HIS、PCA、Brovey及小波变换4种图像融合方法对南京地区植被信息提取过程中ETM 遥感影像进行融合和分类试验。从信息量、高分辨率信息的融入度和分类精度三方面,对融合图像进行光谱质量和空间结构信息的定量评价。试验结果表明,Brovey变换更适合植被信息提取时的ETM 图像融合,并能够较明显提高影像的分类精度。

关 键 词:植被信息  图像融合  分类  试验
修稿时间:2006-09-04

Study on ETM+Remote Sensing Image Fusion and Classification in the Extraction of Vegetation Information
Shen Mingxia,He Ruiyin,Cong Jinghua.Study on ETM+Remote Sensing Image Fusion and Classification in the Extraction of Vegetation Information[J].Transactions of the Chinese Society of Agricultural Machinery,2007,38(8):109-112.
Authors:Shen Mingxia  He Ruiyin  Cong Jinghua
Institution:1.Nanjing Agricultural University 2.Nanjing High School of Forest Police
Abstract: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.
Keywords:Vegetation information  Image fusion  Classification  Experiment
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