ICE: A statistical approach to identifying constituents of biomedical hyperspectral images

被引:3
作者
Berman, M [1 ]
Phatak, A [1 ]
Lagerstrom, R [1 ]
机构
[1] CSIRO, N Ryde, NSW 2113, Australia
来源
Spectral Imaging: Instrumentation, Applications, and Analysis III | 2005年 / 5694卷
关键词
convex geometry; endmember; hyperspectral; mixture; simplex;
D O I
10.1117/12.600291
中图分类号
O433 [光谱学];
学科分类号
0703 ; 070302 ;
摘要
A problem of considerable interest in the hyperspectral and chemical imaging communities in recent years has been the automated identification and mapping of the constituent materials ("endmembers") present in a hyperspectral image. Several of the more important endmember-finding algorithms are discussed and some of their shortcomings highlighted. A relatively new algorithm, ICE, which attempts to address these shortcomings, is introduced. Although ICE was originally developed for exploration applications of airborne hyperspectral data, its performance on two biomedical data sets is investigated. Possible future research directions are outlined.
引用
收藏
页码:62 / 73
页数:12
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