ICE: a statistical approach to identifying endmembers in hyperspectral images |
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| Authors: | Berman M. Kiiveri H. Lagerstrom R. Ernst A. Dunne R. Huntington J.F. |
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| Affiliation: | Macquarie Univ. Campus, North Ryde, NSW, Australia; |
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| Abstract: | Several of the more important endmember-finding algorithms for hyperspectral data are discussed and some of their shortcomings highlighted. A new algorithm - iterated constrained endmembers (ICE) - which attempts to address these shortcomings is introduced. An example of its use is given. There is also a discussion of the advantages and disadvantages of normalizing spectra before the application of ICE or other endmember-finding algorithms. |
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