Using this hyperspectral data, scientists have mapped the location of sulfur deposits on the ice surface (red outline).
使用这个高光谱数据，科学家已经为冰面硫磺沉积物的位置绘制了地图(红色轮廓)。
However, the conventional image analysis methods can not meet the requirements of hyperspectral image applications.
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。
Characterization of a sulfur-rich Arctic spring site and field analog to Europa using hyperspectral data. Remote Sensing of Environment, 114 (6), 1297-1311.
使用高光谱数据描述一个类似于欧罗巴星的北极区富硫泉水地带，《环境遥感》，114（6），1297-1311.
Furthermore, hyperspectral and multispectral image processing is extended with the capacity to analyze additional bands of image data, which minimizes the dependency on specialized software packages.
此外，高光谱和多光谱图像处理能力也得到扩展，可分析额外频段的图像数据，最大限度地减少对专用软件包的依赖。
Furthermore, the method can suppress random noise in the original hyperspectral imagery.
算法还能有效地抑制原始图像中的随机噪声。
Data compression is a key problem in the applications of hyperspectral images.
数据压缩是高光谱图像处理应用中的一个关键问题。
A segmented PCA based band selection algorithm of hyperspectral image is proposed.
提出了一种基于分段主成分分析的高光谱图像波段选择算法。
In fact, however, some researches don't need all information of hyperspectral images.
事实上，有很多高光谱的应用研究并不需要用到高光谱图像的全部信息。
The performance of red tide detection model by airborne hyperspectral data is assessed.
基于显著性度量和检测偏差值评估赤潮航空高光谱检测模型的检测效果。
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。
The technical principle and methods of hyperspectral images pre-processing were described.
详细描述了对超光谱图像进行预处理的技术原理和方法。
Independent Component analysis is a new transform for multispectral or hyperspectral datasets.
是多光谱或超光谱数据集的一种新的转换方法。
A supervised detection algorithm is presented to detect the target region in hyperspectral imagery.
给出一种有监督检测算法以检测高光谱图像中的区域目标。
In this paper, a new method of hyperspectral anomaly detection based on project pursuit is presented.
该文提出了一种基于投影追踪的高光谱图像异常点检测方法。
The application effect of the hyperspectral imaging system heavily relies on the signal to noise ratio.
高光谱成像系统的应用效果非常依赖仪器获取图像的信噪比。
The processing of PHI-3 hyperspectral remote sensing data from original data to production is presented.
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。
At first, adopt the Adaptive Band Selection to compress spectrum dependence of hyperspectral remote sensing image.
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。
Prove hyperspectral remote sensing image relatively stronger spectrum dependence and relatively weaker space dependence.
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。
The hyperspectral remote sensing technology has become one of the leading technologies in forestry remote sensing domain.
高光谱遥感技术已成为林业遥感领域的前沿技术之一。
Therefore, how to effectively interpret mixed pixels is an important problem of hyperspectral remote sensing applications.
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。
However, because of the affection of various factors, hyperspectral images are usually seriously corrupted by stripe noises.
但由于各种因素影响，高光谱图像受到了严重的条带噪声干扰。
A framework was proposed for the selection of wavelength bands for multispectral sensors by use of hyperspectral reference data.
利用超光谱数据对多光谱传感器的波段选择提出了一个框架。
Using fuzzy clustering, the original bands set of hyperspectral remotely sensed images is divided into some fuzzy equivalent subset.
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。
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。
The compression technology of hyperspectral image is a key problem to be solved in the storage and transportation of remote sensing data.
高光谱图像压缩技术是遥感数据存储和传输中的一个迫切需要解决的问题。
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。
Based on the analysis of characteristics of hyperspectral imagery, the methods of anomaly detection are studied systematically in this paper.
本文在深入分析高光谱数据特点的基础上，系统地研究了基于光谱维的图像异常检测方法。
In the hyperspectral image processing, spectral match technique is one of the key techniques to identify and classify the material in the image.
在高光谱图像处理中，光谱匹配技术是高光谱地物识别的关键技术之一。
Atmospheric correction and spectral reconstruction of hyperspectral remote sensing applications is the key technology and necessary prerequisite.
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.
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。
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