An Application-oriented Hyperspectral Classification Scheme 面向应用的成像光谱数据分类技术
hyperspectral remote sensing image classification 高光谱遥感影像分类
Hyperspectral image classification 高光谱图像分类
hyperspectral imagery classification 高光谱图像分类
hyperspectral remote sensing classification 高光谱遥感分类
Matlab Hyperspectral Image Classification ToolboxMatlab 的高光谱影像分类工具箱
Classification is an important means for analysis and application of hyperspectral images.
图像分类是高光谱遥感图像分析与应用的重要手段。
Support Vector Machines(SVM) is a potential hyperspectral remote sensing classification method because it is advantageous to deal with problems with high dimensions, small samples and uncertainty.
支持向量机因其适用高维特征、小样本与不确定性问题的优越性，是一种极具潜力的高光谱遥感分类方法。
Hyperspectral imagery feature extraction and classification is approached by combining with nation's 863-708 project and corresponding scientific assignments.
结合国家863 - 708计划项目和相关科研课题，本论文探讨了高光谱影像特征提取与分类问题。
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