Image Understanding Research at UC Irvine: Automatic Recognition in
Multispectral Imagery
G. Healey
In this project, we will develop and demonstrate new algorithms for
the illumination and temperature invariant recognition of targets in
multispectral infrared images. The algorithms will be based on the use
of invariants computed from image regions. These invariants are derived
from physical models for image formation and are independent of viewpoint
and the illumination, atmospheric, and thermal environments. We have shown
that invariants can be computed that capture arbitrary combinations of
spectral and spatial information allowing spectral/spatial tradeoffs to
be optimized according to the characteristics of a particular recognition
problem. Since the algorithms are derived from physical models, constraints
on the physical environment can be incorporated to improve performance.
Extensive experiments will be conducted to demonstrate the effectiveness
of the approach.
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