Novel hyperspectral prediction method and apparatus

Gabor J. Kemeny; Natalie A. Crothers; Gard A. Groth; Kathy A. Speck; Ralf Marbach

doi:10.1117/12.818955

28 April 2009 Novel hyperspectral prediction method and apparatus

Gabor J. Kemeny, Natalie A. Crothers, Gard A. Groth, Kathy A. Speck, Ralf Marbach

Proceedings Volume 7319, Next-Generation Spectroscopic Technologies II; 731909 (2009) https://doi.org/10.1117/12.818955
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

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-Cal^TM software used for the present work. The prediction algorithms can then be downloaded into a dedicated FPGA based High-Speed Prediction Engine^TM 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.

Citation Download Citation

Gabor J. Kemeny, Natalie A. Crothers, Gard A. Groth, Kathy A. Speck, and Ralf Marbach "Novel hyperspectral prediction method and apparatus", Proc. SPIE 7319, Next-Generation Spectroscopic Technologies II, 731909 (28 April 2009); https://doi.org/10.1117/12.818955

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KEYWORDS

Cameras

Calibration

Spectroscopy

Hyperspectral imaging

Magnesium

Minerals

Statistical analysis

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