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ICE: A Statistical Approach to Identifying Constituents of Biomedical Hyperspectral Images

机译:ICE:一种识别生物医学高光谱图像成分的统计方法

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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.
机译:近年来,在高光谱和化学成像社区中引起相当大兴趣的问题是自动识别和映射高光谱图像中存在的构成材料(“端成员”)。讨论了一些更重要的端成员查找算法,并突出了它们的一些缺点。引入了一种相对较新的算法,ICE,试图解决这些缺点。尽管ICE最初是为机载高光谱数据的勘探应用而开发的,但仍研究了其在两个生物医学数据集上的性能。概述了未来可能的研究方向。

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