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  \textbf{\Large{\textsc{STANFORD UNIVERSITY}}}\\[5pt]
  \textbf{\Large{\textsc{DEPARTMENT OF STATISTICS}}}\\[5pt]
  \Large{\textsc{DEPARTMENTAL SEMINAR}}
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  4:15 p.m., Tuesday, July 15, 2008\\
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  Sequoia Hall Room 200\\
  (Cookies at 3:45 in 1st Floor Lounge)
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  \textsl{Mark Berman} \\
  CSIRO Mathematical and Information Sciences
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  \subsection*{Some Statistical Problems in Spectroscopy and Hyperspectral Imaging}
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\noindent

Every material has a distinctive spectrum. The spectrum of a material tells us
about its chemistry.  Hyperspectral images produce a spectrum (represented as
several hundred numbers) at each pixel in an image. So hyperspectral images
enable us to map variations in chemistry.

The first hyperspectral scanners, built in the 1980ââ¢Ë™s and 1990ââ¢Ë™s, were designed
for airborne applications, primarily for mineral, environmental and military
applications. However, in recent years, hyperspectral microscopes and cameras
have been developed and are being used for terrestrial applications in areas
such as medical diagnosis, burns analysis and skin cancer, biosecurity,
pharmaceuticals, forensics and in agribusiness.

A significant issue in hyperspectral imaging is that the spectra at many pixels
in an image are actually mixtures of the spectra of the pure ingredients. My
main focus over a number of years has been on developing fast and sophisticated
algorithms and software for ââ¢Ë›unmixingââ¢Ë‡ these spectra into their pure
ingredients, both when the pure ingredients are known and when they are
unknown. This has resulted in two software packages:

The Spectral Assistant (TSA), which has been incorporated into another CSIRO
package, The Spectral Geologist, which itself has been sold to over 100 (mainly
exploration and mining) companies around the world; and Iterated Constrained
Endmembers (ICE), which has yet to be commercialized.

I will give an overview of the algorithms underlying TSA and ICE, and
demonstrate their application to some mineral, biological and pharmaceutical
data sets. Finally, I will discuss some unsolved statistical and computational
problems associated with these packages.

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