Also we construe the high data dimension and entropy of hyperspectral image.
高光谱图像的特性是对高光谱图像进行压缩的基础。
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。
Based on linear prediction and arithmetic coding of hyperspectral image compression, and I hope useful for you.
一种基于线性预测和算术编码的高光谱图像压缩方法，希望对您有用。
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。
Experimental results of Hyperspectral image segmentation show that our method is better than traditional spectral Angle mapping method.
高光谱图像分割实验结果表明该方法在光谱相似性度量上优于传统的光谱角制图方法。
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。
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。
There is great redundancy information in hyperspectral image and band selection can effectively remove it and reduce computational cost accordingly.
高光谱图像间存在着大量的冗余信息，波段选择能够有效地去除冗余信息从而减少计算量。
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。
However, each pixel of hyperspectral image has tens or hundreds of magnitude values corresponding its wave bands, so the enormous data must be compressed.
但是高光谱图像的每个像元都对应几十到几百个波段的灰度值，数据量极其庞大，因此必须对其进行压缩。
Because the remotely sensed hyperspectral image information is very precious, the lossless compression or near have lossless compression method is needed possibly.
由于遥感图像信息十分宝贵，应尽可能采用无损压缩或近无损压缩方法。
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。
The relevance vector machine (RVM) is used to process the hyperspectral image in this paper to estimate the classifiers precisely in the high dimensional space with limited training samples.
将关联向量机应用于高光谱影像分类，实现高维空间中训练样本不足时分类器的精确建模。
The sixth chapter summarized the whole thesis and listed the achievement of this study, as same as, pointed out the difficulties in precise inversion of soil characteristics from hyperspectral image.
论文的第六章，主要是对全文进行了概括总结，列举了作者的主要研究进展和在高光谱遥感图像中精确反演土壤特性参数的地难点及其改进之处。
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。
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。
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。
We study on the image information and quantitative analysis focusing on the spectral dimension because the hyperspectral data has the abundant spectral information.
高光谱分辨率遥感数据以其丰富的光谱信息使得其分析处理集中于光谱维上进行图像信息的展开和定量分析。
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 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。
This paper put its emphasis on dimension reduction, the main research contents are as following: the characteristic of hyperspectral remote sensing image is researched.
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。
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 refers to use very narrow and continuous spectrum of remote sensing image features continuous channel of technology.
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。
As an image-spectrum merging technology, hyperspectral imaging has been used in battlefield reconnaissance rapidly.
超光谱成像是一种场景图谱合一的技术，在战场侦察中得到了迅速应用。
As an image-spectrum merging technology, hyperspectral imaging has been used in battlefield reconnaissance rapidly.
超光谱成像是一种场景图谱合一的技术，在战场侦察中得到了迅速应用。
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