A single individual evolutionary strategy for endmember search in hyperspectral images

被引：12

作者：

Graña, M ^{[1
]}

Hernandez, C ^{[1
]}

Gallego, J ^{[1
]}

机构：

[1] Univ Pais Vasco EHU, Fac Informat, Dept CCIA, San Sebastian 20080, Spain

来源：

INFORMATION SCIENCES | 2004年 / 161卷 / 3-4期

关键词：

D O I：

10.1016/j.ins.2003.05.005

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We define an single individual evolutionary strategy (SIE) for the induction of a set of endmembers and we compare it with a conventional evolutionary strategy (ES), tailored to this task, over a couple of hyperspectral images. The SIE considers a set of endmembers as an evolving population. Individuals correspond to hypothetical endmember spectra, and they are selected as candidates for mutation on the basis of their partial abundance images. The population's global fitness when the mutated individual substitutes its parent is the measure of the goodness of the individual. Although the aim of defining the SIE was to reduce the computational cost of applying ES to the high volume data in hyperspectral images, we have found that SIE also improves the fitness performance of conventional ES. (C) 2003 Elsevier Inc. All rights reserved.

引用

页码：181 / 197

页数：17

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