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

J. Bruce Rafert, Jaime Zabalza, Stephen Marshall, Jinchang Ren

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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.
Original languageEnglish
Number of pages10
JournalApplied Spectroscopy
Publication statusPublished - 4 May 2016


  • hyperspectral imagers
  • Fourier transform
  • data processing


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