This paper reports instrument characterization measurements, which were recently arranged to provide comparative
information on different hyperspectral chemical imaging systems. Three different instruments were studied covering
both tunable filter and push-broom techniques: The first instrument MatrixNIRTM is based on a LCTF tunable filter and
InGaAs camera and covers wavelengths from 1000 to 1700 nm. The second one SisuCHEMATM is based on push-broom
technology and MCT camera operating from 1000 to 2500 nm. The third system is an instrument prototype from VTT
Technical Research Centre of Finland exploiting high speed Fabry-Perot interferometer and MCT camera, currently
calibrated from 1260 to 2500 nm. The characterization procedure was designed to study instrumental noise, signal-to-noise
ratio, linearity and spectral as well as spatial resolution. Finally, a pharmaceutical tablet sample was measured with
each instrument to demonstrate speed of measurement in a typical application. In spite of differences in wavelength
ranges and camera technologies used, the results provide interesting information on relative instrumental advantages and
disadvantages, which may be useful for selecting appropriate instrumentation for defined applications. Further, an
additional aim of this study is to compare the high speed Fabry-Perot imaging technology under development against the
established chemical imaging techniques available on the market today.
Both the power and the challenge of hyperspectral technologies is the very large amount of data produced by spectral
cameras. While off-line methodologies allow the collection of gigabytes of data, extended data analysis sessions are
required to convert the data into useful information. In contrast, real-time monitoring, such as on-line process control,
requires that compression of spectral data and analysis occur at a sustained full camera data rate. Efficient, high-speed
practical methods for calibration and prediction are therefore sought to optimize the value of hyperspectral imaging.
A novel method of matched filtering known as science based multivariate calibration (SBC) was developed for
hyperspectral calibration. Classical (MLR) and inverse (PLS, PCR) methods are combined by spectroscopically
measuring the spectral "signal" and by statistically estimating the spectral "noise." The accuracy of the inverse model is
thus combined with the easy interpretability of the classical model. The SBC method is optimized for hyperspectral data
in the Hyper-CalTM software used for the present work. The prediction algorithms can then be downloaded into a
dedicated FPGA based High-Speed Prediction EngineTM module. Spectral pretreatments and calibration coefficients are
stored on interchangeable SD memory cards, and predicted compositions are produced on a USB interface at real-time
camera output rates. Applications include minerals, pharmaceuticals, food processing and remote sensing.
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