Abstract
Static Fourier transform spectrometers require, especially in the infrared, a spatial calibration step. Unfortunately, the superposition of fringes on the measured images has a major impact on spatial calibration and therefore on the returned spectra. We first study how to pre-process images so that spectral errors are minimized. Then, we develop a spectrum formation model that is used to correct those spectral errors. The performance, evaluated on synthetic data, is remarkable and theoretically justifies the use of this calibration concept.
Highlights
Fourier Transform Infrared Spectrometers (FTIR) are unparalleled tools for extracting as much spectral information as possible above the visible spectrum [1]
The origin of all the difficulties lies in the derived nature of spectrum measurements, which means that stringent conditions are necessary to comply with the requirements of the Fourier transform used to generate the spectra
We developed an airborne Imaging Infrared Static Fourier Transform Spectrometer, called Sieleters [9] which comes in two flavors; MWIR and LWIR
Summary
Fourier Transform Infrared Spectrometers (FTIR) are unparalleled tools for extracting as much spectral information as possible above the visible spectrum [1]. Instead of temporally exploring the optical path difference (OPD) it makes sense to spatially spread the OPD over a detector array. This instrument concept has been the subject of numerous studies since the first article of 1965 by Stroke&Funkhouser [2] but has seen few real working instruments [3,4,5,6,7,8,9] and even less evidence of high signal to noise spectrum measures [10,11]. The origin of all the difficulties lies in the derived nature of spectrum measurements, which means that stringent conditions are necessary to comply with the requirements of the Fourier transform used to generate the spectra. The analysis will be based on synthetic data in order to compare our results with the underlying truth, which is difficult to find on real acquisitions
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