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。
The article used absolute exponent as one of the methods of fuzzy diagnosis to identify and classify hyperspectral images, then evaluated precision of classification result based on pixel level.
文中采用模糊识别的绝对值指数法对高光谱图像进行识别分类，并对分类结果进行像元级的评价。
According to the rice spectral features of hyperspectral image data acquired during the rice is growing, a hybrid decision tree classification algorithm dealing with the variety of rice is developed.
根据水稻生长期的高光谱数据的光谱特征，设计了一个混合决策树分类算法。
In order to improve the classification accuracy of hyperspectral images, a fuzzy maximum likelihood classification method is proposed.
为了提高超谱图像分类的精度，提出了模糊最大似然分类算法。
However, classifying hyperspectral images only with traditional classification algorithms will result in low classification precision, data redundancy and great waste of resource.
但仅用传统分类算法对高光谱图像分类，会导致分类精度降低、空间数据冗余和资源的极大浪费。
Moreover, compared with the conventional unsupervised classification algorithm of hyperspectral data, the proposed algorithm is more applicable and can obtain the better precision and accuracy.
与传统高光谱无监督分类算法比较，表明该算法的适用性，并具有更高的分类精度和准确性。
The hyperspectral remote sensing image is rich in spectrum information, so it can be better to carry on the ground targets classification.
高光谱遥感影像具有丰富的光谱信息，在地物分类识别方面具有明显的优势。
The study on the hyperspectral image classification is valuable to crop growth monitoring, mineral identification and seawater analysis as well as many other useful aspects.
超谱遥感图像的分类研究对农作物生长状况的监测、矿物的识别、海洋水色分析以及其他方面的许多应用都是很有价值的。
In the hyperspectral remote sensing, the continuum removed methods is used only with the spectrum of a single pixel to analyze spectrum and extract the feature bands useful with the classification.
在高光谱遥感中，包络线消除法一般仅局限于对单个像元的光谱进行光谱分析，从中提取出有助于分类识别的特征波段。
In the hyperspectral remote sensing, the continuum removed methods is used only with the spectrum of a single pixel to analyze spectrum and extract the feature bands useful with the classification.
在高光谱遥感中，包络线消除法一般仅局限于对单个像元的光谱进行光谱分析，从中提取出有助于分类识别的特征波段。
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