ICE: An automated statistical approach to identifying endmembers in hyperspectral images

被引：0
|
作者：
Berman, M [1 ]
Kiiveri, H [1 ]
Lagerstrom, R [1 ]
Ernst, A [1 ]
Dunne, R [1 ]
Huntington, J [1 ]
机构：
[1] CSIRO Math & Informat Sci, N Ryde, NSW 2113, Australia
来源：
IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES | 2003年
关键词：
D O I：
暂无
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Several of the more important endmember-finding algorithms for hyperspectral data are discussed and their shortcomings highlighted. A new algorithm, ICE, which attempts to overcome these shortcomings is introduced. An example of its use is given.
引用
收藏
页码：279 / 283
页数：5
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