Singular spectrum analysis : a note on data processing for Fourier transform hyperspectral imagers
Rafert, J. Bruce and Zabalza, Jaime and Marshall, Stephen and Ren, Jinchang (2016) Singular spectrum analysis : a note on data processing for Fourier transform hyperspectral imagers. Applied Spectroscopy. ISSN 0003-7028
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Abstract
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.
ORCID iDs
Rafert, J. Bruce, Zabalza, Jaime ORCID: https://orcid.org/0000-0002-0634-1725, Marshall, Stephen ORCID: https://orcid.org/0000-0001-7079-5628 and Ren, Jinchang ORCID: https://orcid.org/0000-0001-6116-3194;-
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Item type: Article ID code: 55647 Dates: DateEvent4 May 2016Published2 February 2016AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset ManagementDepositing user: Pure Administrator Date deposited: 22 Feb 2016 16:59 Last modified: 11 Nov 2024 11:20 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/55647