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A survey on fundamental concepts and practical challenges of Hyperspectral images

机译:高光谱图像基本概念和实际挑战调查

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The Remote sensing provides a synoptic view of land by detecting the energy reflected from Earth's surface. The Hyperspectral images (HSI) use perfect sensors that extract more than a hundred of images, with more detailed information than using traditional Multispectral data. In this paper, we aim to study this aspect of communication in the case of passive reception. First, a brief overview of acquisition process and treatment of Hyperspectral images is provided. Then, we explain representation spaces and the various analysis methods of these images. Furthermore, the factors influencing this analysis are investigated and some applications, in this area, are presented. Finally, we explain the relationship between Hyperspectral images and Datamining and we outline the open issues related to this area. So we consider the case study: HSI AVIRIS 92AV3C. This study serves as map of route for integrating classification methods in the higher dimensionality data.
机译:遥感通过检测从地球表面反射的能量来提供土地的概要视图。高光谱图像(HSI)使用完美的传感器,可以提取一百多幅图像,并且比使用传统的多光谱数据提供更详细的信息。在本文中,我们旨在研究无源接收情况下通信的这一方面。首先,简要概述了高光谱图像的采集过程和处理。然后,我们解释这些图像的表示空间和各种分析方法。此外,研究了影响该分析的因素,并介绍了该领域的一些应用。最后,我们解释了高光谱图像与数据挖掘之间的关系,并概述了与此领域相关的未解决问题。因此,我们考虑案例研究:HSI AVIRIS 92AV3C。这项研究可作为将分类方法集成到高维数据中的路线图。

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