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Singular spectrum analysis : a note on data processing for Fourier transform hyperspectral imagers

机译:奇异光谱分析:有关傅里叶变换高光谱成像仪数据处理的说明

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摘要

Hyperspectral remote sensing is experiencing a dazzling proliferation of new sensors, platforms, sys tems, and applications with the introduction of novel, low cost, low weight sensors. Curiously, relatively little development is now occurring in the use of Fourier Transform (FT) systems, which have the potential to operate at extremely high throughput wi thout use of a slit or reductions in both spatial and spectral resolution that thin film based mosaic sensors introduce. This study introduces a new physics - based analytical framework called Singular Spectrum Analysis (SSA) to process raw hyperspectral ima gery collected with FT imagers that addresses some of the data processing issues associated with FT instruments including the need to remove low frequency variations in the interferogram that are introduced by the optical system, as well as high frequency variations that lay outside the detector band pass. Synthetic interferogram data is analyzed using SSA, which adaptively decomposes the original synthetic interferogram into several independent components associated with the signal, photon and system nois e, and the field illumination pattern.
机译:高光谱遥感通过引入新型,低成本,轻巧的传感器,正在经历着新传感器,平台,系统和应用的惊人增长。奇怪的是,现在使用傅立叶变换(FT)系统的发展相对较少,而无需使用狭缝或降低基于薄膜的镶嵌传感器带来的空间分辨率和光谱分辨率,它们有可能以极高的吞吐量运行。 。这项研究引入了一种基于物理学的新分析框架,称为奇异频谱分析(SSA),用于处理用FT成像仪收集的原始高光谱图像,该图像框架解决了与FT仪器相关的一些数据处理问题,包括需要消除干涉图中的低频变化光学系统引入的噪声以及检测器带通之外的高频变化。使用SSA分析了合成干涉图数据,SSA将原始合成干涉图自适应地分解为与信号,光子和系统噪声以及场照明模式相关的几个独立分量。

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