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Is Hyperspectral Imaging an Analytical Instrument?

Paul Geladi feb 06

Paul Geladi

Head of Research NIRCEChairperson NIR Nord

Unit of Biomass Technology and ChemistrySwedish University of Agricultural SciencesUmeåTechnobothniaVasa

paul.geladi @ btk.slu.se paul.geladi @ uwasa.fi

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Paul Geladi feb 06

Content

• Short introduction of the topic

• Space imaging

• Instrumentation

• Examples, history and philososphical thoughts

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Multivariate Image

K << I ≈ J

I

J

K

I

J

K

HyperspectralImageK≈I≈J

What is a hyperspectral image?

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256

320

128

512

614

224

MatrixNIR

AVIRIS

First defined in airborne imaging

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Na Mg

Al Si

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Cr Fe

Ni

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Cu Zn

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

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Airborne hyperspectral imaging•http://www.microimages.com/getstart/hyprspec.htm

• Randall Smith 2001

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Some airborne systems

Sensor Country Nr bands Range m

AVIRIS USA 224 0.4 - 2.5

AISA FI 286 0.45 - 0.9

CASI CA 288 0.43 - 0.87

DAIS USA 211 0.4 - 12

HYMAP AU 128 0.4 - 2.45

PROBE1 USA 128 0.4 - 2.45

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Orig

Veg

Water

Soil

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Conclusions Airborne

• Not too much chemometrics

• Calibration / standardization / correction problems

• Comparison of airborne / ground spectra

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0 nm 3000 nm

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Lab versus airplane

• We have our own “sun”

• It is controllable

• Only within limits

• Problems still exist

• How to quantify / correct problems?

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Content

• Short introduction of the topic

• Space imaging

• Instrumentation

• Examples, history and philososphical thoughts

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AVIRIS

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Rotating filter wheel

Camera

Filter wheel

Field of study under polychromatic illumination

Signal out

Alternative: illumination diode array

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PbS camera

Fiber ring

Radiation source

Interference filters

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680 nm 740 nm 800 nm 840 nm

1010 nm 1110 nm 1200 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, 1347-1357, 2004.

Paul Geladi feb 06Prism-Grating -Prism

Prism

Grating

Prism

Focusing

Focusing

Rectangulardetector

Pushbroom

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Interferometer

Fixed mirror

Moving mirror

Semitransparentmirror (50%)

Detector(interferogram)

a

b

Sample (scan by moving)

Radiationsource

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Most FT-IRFT-Raman

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InGaAs array

LCTF

Objective

Sample(s)

Lamp(s)

≈5 cm

≈5 cm

To file

12 bit A/D convertor

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InGaAs array

LCTF

Objective

Sample(s)

Lamp(s)

≈5 cm

≈5 cm

To file

12 bit A/D convertor

256x3200.2x0.2 mm2 pixel

max 128 900-1700 nm

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Content• Short introduction of the topic

• Examples, history and philososphical thoughts

• Standardization

• Calibration

• Sampling problems

• Comparison

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Edmundcatalog

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900 1000 1100 1200 1300 1400 1500 1600 17000

500

1000

1500

2000

2500

3000

3500

4000

4500

wavelength nm

A/D counts

Specular reflection

99%

2%

75%

50%

Raw A/D convertor data

Paul Geladi feb 06900 1000 1100 1200 1300 1400 1500 1600 1700

50

50.5

51

51.5

52

52.5

53

53.5

54

54.5

55

wavelength nm

Reflectance %

NIST calibration

Interpolation

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2%

25%

50%

75%

99%

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R= 1, 0.8, 0.6, 0.4

R= 0.2, 0.1, 0.05, 0

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Content• Short introduction of the topic

• Examples, history and philososphical thoughts

• Standardization

• Calibration

• Sampling problems

• Comparison

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Metal frame

2% refl.

50% refl. 75% refl.

99% refl.

Cheddar

Blue

Edam

Emmenthal

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Reference values (y)

• Pure standards

• Known mixtures

• Wet chemistry

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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, 209-217, 2004.

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Content• Short introduction of the topic

• Space imaging

• Instrumentation

• Examples, history and philososphical thoughts

• Standardization

• Calibration

• Sampling problems

• Comparison

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One pixel

50/50 mixture

Sampling problem

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One pixel

50/50 mixture

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Content• Short introduction of the topic

• Examples, history and philososphical thoughts

• Standardization

• Calibration

• Sampling problems

• Comparison

• Examples (removed, paper in review)

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Comparison with a spectrometer

• Integration over a volume / area

• Only 1 detector• High resolution 216

• Wide range possible• Lower noise

• Information in pixels / depth?

• Many detectors• Low resolution 212

• Limited range• Noisier

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Comparison

• Linearity better controlled

• No populations• Quick

• Linear?• Missing pixels• Populations!• Slow

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Conclusions

• Airborne/space are ahead

• Many principles

• Instrument standardization needed

• No material is homogeneous at the nanolevel

• Camera ≠ spectrometer, but we get close

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Acknowledgements

Torbjörn Lestander, SLU, Umeå

Jim Burger, SLU, Umeå

EASIM European Association for Spectral Imaging

started in Umeå 14 February 2006

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