ICE: An Automated Statistical Approach to Identifying Endmembers in Hyperspectral Images

Mark Berman, Harri Kiiveri, Ryan Lagerstrom, Andreas Ernst, Rob Dunne, Jon Huntington

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

5 Citations (Scopus)

Abstract

Several of the more important endmember-finding algorithms for hyperspectral data are discussed and their short-comings highlighted. A new algorithm, ICE, which attempts to overcome these shortcomings is introduced. An example of its use is given.

Original languageEnglish
Title of host publicationInternational Geoscience and Remote Sensing Symposium (IGARSS)
Pages279-283
Number of pages5
Volume1
Publication statusPublished - 2003
Externally publishedYes
EventIEEE International Geoscience and Remote Sensing Symposium 2003 - Toulouse, France
Duration: 21 Jul 200325 Jul 2003
https://ieeexplore.ieee.org/xpl/conhome/9010/proceeding?isnumber=28601 (Proceedings)

Conference

ConferenceIEEE International Geoscience and Remote Sensing Symposium 2003
Abbreviated titleIGARSS 2003
CountryFrance
CityToulouse
Period21/07/0325/07/03
Internet address

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