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。
A simplified algorithm of nonlinear principal curves called nonlinear principal poly line is developed and its effect for feature extraction of hyperspectral data is researched.
并对非线性主折线算法用于高光谱遥感数据特征提取的效果进行研究和讨论。
Feature extraction is an indispensable preprocessing step for large and high redundancy data of hyperspectral remote sensing image.
针对高光谱遥感影像数据量大、数据冗余度高的特点，引入拉普拉斯特征映射方法对高光谱遥感数据进行非线性降维。
Hyperspectral remote sensing is a new technology, and this technology brings people strongly method of accurately-identify surface feature by means of acutely ability of spectral feature detecting.
高光谱遥感是一种全新的遥感技术，这项技术以其敏锐的光谱特征探测能力为人们精确认识地物属性提供了强有力的手段。
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。
A fractal feature may be analyzed spectrally and spatially due to the "combination of spectrum and image" character inhered in hyperspectral images.
高光谱影像具有“谱像合一”的特征，因而可以从谱和像两个角度对高光谱影像进行分形分析。
A fractal feature may be analyzed spectrally and spatially due to the "combination of spectrum and image" character inhered in hyperspectral images.
高光谱影像具有“谱像合一”的特征，因而可以从谱和像两个角度对高光谱影像进行分形分析。
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