高光谱遥感具有快速，经济，精确的特点。
The hyper spectral remote sensing characterized with high-speed, cheap, accurateness.
最后对林业高光谱遥感技术的应用前景作了展望。
Finally, the application prospect of hyperspectral remote sensing technology in forestry was analyzed.
图像分类是高光谱遥感图像分析与应用的重要手段。
Classification is an important means for analysis and application of hyperspectral images.
高光谱遥感技术已成为林业遥感领域的前沿技术之一。
The hyperspectral remote sensing technology has become one of the leading technologies in forestry remote sensing domain.
提出一种对高光谱遥感影像波段集合进行整体缩减的方法。
In this paper, a rough sets based global reduction approach, which is suitable for imaging spectrometer image is proposed.
提出一种基于分布异常的高光谱遥感影像小目标检测方法。
This paper presents a small targets detection approach based on anomaly distributing in hyperspectral data.
第三部分利用高光谱遥感资料研究海岸带沙滩表面承载特性。
In the third part, mainly study on sand beach surface characteristic of bearing capacity by hyperspectral remote sensing data.
然而，传统的影像分析方法并不能满足高光谱遥感的应用需求。
However, the conventional image analysis methods can not meet the requirements of hyperspectral image applications.
首先采用自适应波段选择方法对高光谱遥感图像进行谱间压缩。
At first, adopt the Adaptive Band Selection to compress spectrum dependence of hyperspectral remote sensing image.
因此，如何有效地解译混合像元是高光谱遥感应用的突出问题。
Therefore, how to effectively interpret mixed pixels is an important problem of hyperspectral remote sensing applications.
验证了高光谱遥感图像较强的谱间相关性和较弱的空间相关性。
Prove hyperspectral remote sensing image relatively stronger spectrum dependence and relatively weaker space dependence.
将以上两个部分耦合就可得到完整的林地复杂高光谱遥感场景模型。
In this dissertation, two models for hyperspectral remote sensing scene are built.
高光谱遥感是指利用很窄而连续的光谱通道对地物遥感成像的技术。
Hyperspectral remote sensing refers to use very narrow and continuous spectrum of remote sensing image features continuous channel of technology.
通过模糊聚类，得到对高光谱遥感影像原始波段集合的模糊等价划分。
Using fuzzy clustering, the original bands set of hyperspectral remotely sensed images is divided into some fuzzy equivalent subset.
高光谱遥感影像包含了丰富的光谱特征，为精确的变化检测提供了依据。
Hyperspectral remote sensing images contain abundant spectral information for accurate change detection.
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 hyperspectral remote sensing image is rich in spectrum information, so it can be better to carry on the ground targets classification.
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。
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.
高光谱遥感大气校正和光谱重建技术是高光谱遥感应用的关键技术和必要前提。
Atmospheric correction and spectral reconstruction of hyperspectral remote sensing applications is the key technology and necessary prerequisite.
主要介绍PHI - 3高光谱遥感数据从原始数据到产品这一阶段的预处理情况。
The processing of PHI-3 hyperspectral remote sensing data from original data to production is presented.
实验结果表明，本文给出的高光谱遥感影像优化分类波段组合选择方法是非常有效的。
The experiment results indicate that the optimal classification bands combination selecting approach supplied in this paper is quite effective.
一种高光谱遥感数据多类别监督分类方法，包含以下步骤：（1）读入 高光谱数据；
The invention relates to a supervised classification method of multi-class hyperspectrum remotely sensed data, which comprises the following steps: (1), reading the hyperspectrum data;
与常规遥感相比，高光谱遥感数据处理及目标地物的识别需要采用一些新的技术和手段。
Compared with traditional remote sensing, some new technique and method must be developed for hyperspectral remote sensing data processing and object discerning.
另外，根据图像特征和经验对图像进行波段选择，也是改善高光谱遥感分类效果的有效途径。
In addition, the spectral selection based on the image's feature and experience is also an effective way to improve the classification of hyper-spectral remote sensing images.
最后探讨了高光谱遥感数据的五种常用分类方法及分类预处理步骤，为后续工作提供一些思路。
Following the presentation of the fieldwork results, the paper discusses five prevailing classification methods and steps for pre-processing, providing some ideas for following work.
高光谱遥感是一门将反映地物辐射属性的光谱与反映地物空间和几何关系的图像结合在一起的技术。
Hyperspectral remote sensing is an art, which integrates the spectrum representing to the radiant attributes of ground object with the homological images standing for spatial and geometric relations.
文章深入分析了高光谱遥感数据中噪声的特点，提出了一种基于平稳小波变换的改进小波滤噪算法。
This paper analyzed the characteristic of noise in hyperspectral data deeply, and puts forward a de-noising method based on stationary discrete wavelet transform (SDWT).
本文重点研究了高光谱遥感图像的降维方法，研究的主要内容如下：研究了高光谱遥感图像的特性。
This paper put its emphasis on dimension reduction, the main research contents are as following: the characteristic of hyperspectral remote sensing image is researched.
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。
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.
植被高光谱遥感以其显著的特点已经成为连接遥感数据处理、地面测量、光谱模型和应用的强有力的工具。
Hyperspectral remote sensing data, compared with wide band remote sensing data, has the advantage of high spectral resolution.
植被高光谱遥感以其显著的特点已经成为连接遥感数据处理、地面测量、光谱模型和应用的强有力的工具。
Hyperspectral remote sensing data, compared with wide band remote sensing data, has the advantage of high spectral resolution.
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