Paul Geladi feb 06 Is Hyperspectral Imaging an Analytical Instrument?

Paul Geladi feb 06 Paul Geladi Head of Research NIRCE Chairperson NIR Nord Unit of Biomass Technology and Chemistry Swedish University of Agricultural Sciences Umeå Technobothnia Vasa btk.slu.se uwasa.fi

Paul Geladi feb 06

Content Short introduction of the topic Space imaging Instrumentation Examples, history and philososphical thoughts

Paul Geladi feb 06 Multivariate Image K << I ≈ J I J K I J K Hyperspectral Image K≈I≈J What is a hyperspectral image?

Paul Geladi feb MatrixNIR AVIRIS First defined in airborne imaging

Paul Geladi feb 06 Na Mg AlSi

Paul Geladi feb 06 CrFe Ni

Paul Geladi feb 06 Cu Zn Van Espen P., Janssens G., Vanhoolst W. & Geladi P., Imaging and image processing in analytical chemistry, Analusis, 20, 81-90, 1992.

Paul Geladi feb 06 Airborne hyperspectral imaging Randall Smith 2001

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Some airborne systems SensorCountryNr bands Range  m AVIRISUSA AISAFI CASICA DAISUSA HYMAPAU PROBE1USA

Paul Geladi feb 06 Orig Veg Water Soil

Paul Geladi feb 06 Conclusions Airborne Not too much chemometrics Calibration / standardization / correction problems Comparison of airborne / ground spectra

Paul Geladi feb 06 0 nm 3000 nm

Paul Geladi feb 06 Lab versus airplane We have our own “sun” It is controllable Only within limits Problems still exist How to quantify / correct problems?

Paul Geladi feb 06 Content Short introduction of the topic Space imaging Instrumentation Examples, history and philososphical thoughts

Paul Geladi feb 06 AVIRIS

Paul Geladi feb 06 Rotating filter wheel Alternative: illumination diode array

Paul Geladi feb 06 PbS camera Fiber ring Radiation source Interference filters

Paul Geladi feb nm 740 nm800 nm 840 nm 1010 nm1110 nm1200 nm Geladi P, Sethson B, Nyström J, Lillhonga T, Lestander T & Burger J, Chemometrics in spectroscopy: Part 2. Examples, Spectrochimica Acta Part B: Atomic Spectroscopy, 59, , 2004.

Paul Geladi feb 06 Prism-Grating -Prism Pushbroom

Paul Geladi feb 06 Interferometer Fixed mirror Moving mirror Semitransparent mirror (50%) Detector (interferogram) a b Sample (scan by moving) Radiation source

Paul Geladi feb 06 Most FT-IR FT-Raman

Paul Geladi feb 06 InGaAs array LCTF Objective Sample(s) Lamp(s) ≈5 cm To file 12 bit A/D convertor

Paul Geladi feb 06 InGaAs array LCTF Objective Sample(s) Lamp(s) ≈5 cm To file 12 bit A/D convertor 256x x0.2 mm 2 pixel max nm

Paul Geladi feb 06

Content Short introduction of the topic Examples, history and philososphical thoughts Standardization Calibration Sampling problems Comparison

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Edmund catalog

Paul Geladi feb 06

wavelength nm A/D counts Specular reflection 99% 2% 75% 50% Raw A/D convertor data

Paul Geladi feb 06 wavelength nm Reflectance % NIST calibration Interpolation

Paul Geladi feb 06

2% 25% 50% 75% 99%

Paul Geladi feb 06

R= 1, 0.8, 0.6, 0.4 R= 0.2, 0.1, 0.05, 0

Paul Geladi feb 06 Content Short introduction of the topic Examples, history and philososphical thoughts Standardization Calibration Sampling problems Comparison

Paul Geladi feb 06 Metal frame 2% refl. 50% refl. 75% refl. 99% refl. Cheddar Blue Edam Emmenthal

Paul Geladi feb 06 Reference values (y) Pure standards Known mixtures Wet chemistry

Paul Geladi feb 06 Reference values Impossible to measure wet chemistry in every pixel All standards are heterogeneous at high magnification Not always possible with synthetic standards Geladi P., Burger J. & Lestander T., Hyperspectral imaging: calibration problems and solutions, Chemometrics and Intelligent Laboratory Systems, 72, , 2004.

Paul Geladi feb 06 Content Short introduction of the topic Space imaging Instrumentation Examples, history and philososphical thoughts Standardization Calibration Sampling problems Comparison

Paul Geladi feb 06 One pixel 50/50 mixture Sampling problem

Paul Geladi feb 06 One pixel 50/50 mixture

Paul Geladi feb 06

Content Short introduction of the topic Examples, history and philososphical thoughts Standardization Calibration Sampling problems Comparison Examples (removed, paper in review)

Paul Geladi feb 06 Comparison with a spectrometer Integration over a volume / area Only 1 detector High resolution 2 16 Wide range possible Lower noise Information in pixels / depth? Many detectors Low resolution 2 12 Limited range Noisier

Paul Geladi feb 06 Comparison Linearity better controlled No populations Quick Linear? Missing pixels Populations! Slow

Paul Geladi feb 06 Conclusions Airborne/space are ahead Many principles Instrument standardization needed No material is homogeneous at the nanolevel Camera ≠ spectrometer, but we get close

Paul Geladi feb 06 Acknowledgements Torbjörn Lestander, SLU, Umeå Jim Burger, SLU, Umeå EASIM European Association for Spectral Imaging started in Umeå 14 February 2006

Paul Geladi feb 06