A Mathematical Morphology Based Approach to Locating Spectral Endmembers
Spectral endmembers are needed in order to apply Spectral Mixture Analysis (SMA)
based on imaging spectrometer data. Currently there are several techniques able to
find image endmembers in N spectral dimensions and are wholly based on the
spectral feature space. However, modelling only the outside hull of the spectral
scatter provides only a basic understanding of the spectral variability. Our ultimate
goal is to model the n-dimensional spectral space from the inside, out thereby providing a map of image spectral objects. The research presented in this paper are
initial findings applying mathematical morphology to imaging spectrometer data.
Mathematical morphology was applied in two ways: i) by measuring the morphological
hyperspectral scalar gradient at each pixel position using a structuring element
of predefined size and shape and ii) by determining whether this pixel falls within the
smallest enclosing hyperbox containing the pixels belonging to the structuring element
centred at this position. While the results are interesting in themselves, they
were unable to automatically provide the image endmembers. However, the results
provide a wealth of information on the local variations in spectral profiles which will
be used to model their behaviour within the spectral feature cloud.
BIELSKI Conrad;
SOILLE Pierre;
2006-01-20
EARSEL & WARSAW UNIVERSITY
JRC32040
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