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高光谱遥感数据光谱特征的提取与应用
Study on the Extraction and Applications of Spectral Features in Hyperspectral Remote Sensing
【摘要】 基于特征属性与算法原理,提出高光谱遥感光谱特征体系包括光谱曲线特征、光谱变换特征和光谱度量特征三个层次,光谱曲线特征包括直接光谱编码、光谱反射与吸收特征,光谱变换特征包括植被指数、导数光谱、光谱运算特征,光谱度量特征则包括光谱角、光谱信息散度(SID)、相关系数和距离,系统比较分析了不同特征的算法原理、特点、适用情况和应用中的一些问题。
【Abstract】 According to the properties and computation principles, spectral features in hyperspectral remote sensing (RS) information can be grouped into three levels: spectral curve features, spectral transformation features and spectral measurement features. Spectral curve features mainly include direct spectra encoding, reflection and absorption features. Spectral transformation features include normalized difference of vegetation index (NDVI), derivate spectra and spectral computation features. Spectral measurement features include spectral angle (SA), spectral information divergence (SID), spectral distance and correlation index. Based on the analysis to those basic algorithms, several problems about feature extraction, matching and application were discussed.
【Key words】 hyperspectral remote sensing; spectral feature; feature extraction;
- 【文献出处】 中国矿业大学学报 ,Journal of China University of Mining & Technology , 编辑部邮箱 ,2003年05期
- 【分类号】P237
- 【被引频次】129
- 【下载频次】2223