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Imaging Spectroscopy@NICTA
With the advent of new camera technologies, imaging spectroscopy is now becoming available for land-based,
close range inspection and image acquisition. This opens-up a wide variety of opportunities including applications
in recycling, health, environmental management, and, eventually, in professional and consumer photography.
At NICTA, we are working to advance Australian capabilities in key emerging imaging and sensing technologies
beyond the visible spectrum with a strong focus in national prosperity and well being.
We are developing technologies so as to exploit the opportunities, application areas and challenges involving the
use of imaging spectroscopy as a means for scene understanding. This is important, since scene
analysis in the scope of imaging spectroscopy involves the ability to robustly encode material
properties, object composition and concentrations of primordial components in the scene. The
combination of spatial and compositional information opens-up a vast number of application
possibilities.
Spectroscopic scene analysis can enable advanced capabilities for
surveillance by permitting objects to be tracked based on material properties. In computational
photography, images may be enhanced taking into account each specific material type in the
scene. For food security, health and precision agriculture advanced statistical photometric
techniques and software for processing spectral image data can be the basis for the development
of diagnostic and surveying tools which can detect pests before symptoms are apparent to the
naked eye.
This combination of a broad domain of application with the use of key technologies
makes the use of imaging spectroscopy a worthwhile opportunity for researchers in the areas
of computer vision and pattern recognition. At the ISSA project, we are developing
for functions such as material classification, surface structure analysis and constituent component analysis. Combining new
spectral cameras and NICTA’s technology opens up many new applications in many industries.
Our research has a twofold aim. Firstly, addressing
the photometric invariance problem so as to recover features devoid of illumination variations,
specularities and shadowing. Secondly, we aspire to explore the use of the imaging spectra for purposes of scene
and object material classification.
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