@book{JRC32040,
	editor = {},
	address = {WARSAW 2005},
	year = {2006},
	author = {Bielski C and Soille P},
	isbn = {},
	abstract = {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.
		},
	title = {A Mathematical Morphology Based Approach to Locating Spectral Endmembers},
	url = {},
	volume = {},
	number = {},
	journal = {},
	pages = {},
	issn = {},
	publisher = {EARSEL & WARSAW UNIVERSITY},
	doi = {}
}