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Thermal infrared hyperspectral dimension reduction experiment results for global and local information based linear discriminant analysis

机译:热红外高光谱尺寸减少实验结果,基于全局和局部信息的线性判别分析

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摘要

Thermal infrared hyperspectral image processing has become an important research topic in remote sensing. One of the research topics in thermal infrared hyperspectral image classification is dimension reduction. In this paper, thermal infrared hyperspectral dimension reduction experiment results for global and local information based linear discriminant analysis is presented. Advantages of the use of not only global pattern information, but also local pattern information are tested in thermal infrared hyperspectral image processing.
机译:热红外高光谱图像处理已成为遥感中的重要研究主题。热红外高光谱图像分类中的研究主题之一是减少尺寸。本文介绍了基于全局和局部信息的线性判别分析的热红外高光谱尺寸还原实验结果。不仅使用全局模式信息的优点,还可以在热红外高光谱图像处理中测试本地模式信息。

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