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Soft Computing

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06.11.2014 | Focus

Band selection for hyperspectral images using probabilistic memetic algorithm

verfasst von: Liang Feng, Ah-Hwee Tan, Meng-Hiot Lim, Si Wei Jiang

Erschienen in: Soft Computing | Ausgabe 12/2016

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Abstract

Band selection plays an important role in identifying the most useful and valuable information contained in the hyperspectral images for further data analysis such as classification, clustering, etc. Memetic algorithm (MA), among other metaheuristic search methods, has been shown to achieve competitive performances in solving the NP-hard band selection problem. In this paper, we propose a formal probabilistic memetic algorithm for band selection, which is able to adaptively control the degree of global exploration against local exploitation as the search progresses. To verify the effectiveness of the proposed probabilistic mechanism, empirical studies conducted on five well-known hyperspectral images against two recently proposed state-of-the-art MAs for band selection are presented.

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Titel: Band selection for hyperspectral images using probabilistic memetic algorithm
verfasst von: Liang Feng
Ah-Hwee Tan
Meng-Hiot Lim
Si Wei Jiang
Publikationsdatum: 06.11.2014
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 12/2016
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-014-1508-1

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