论文标题
关于高光谱图像的基本概念和实际挑战的调查
A Survey on Fundamental Concepts and Practical Challenges of Hyperspectral images
论文作者
论文摘要
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，这些传感器比使用传统的多光谱数据，具有提取一百多个图像的完美传感器。在本文中，我们旨在研究被动接收的情况下的交流方面。首先，提供了对高光谱图像的获取过程和处理的简要概述。然后，我们解释了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，并提出了该领域的某些应用。最后，我们解释了高光谱图像和数据绘制之间的关系，并概述了与该领域相关的开放问题。因此，我们考虑案例研究：HSI AVIRIS 92AV3C。这项研究是将分类方法整合到更高维度数据中的路线图。 关键字组件：高光谱图像，被动感应，分类，数据挖掘。
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. Keywords-component: Hyperspectral images, Passive Sensing,Classification, Data mining.
