Maximum simplex volume: an efficient unsupervised band selection method for hyperspectral image

Maximum simplex volume: an efficient unsupervised band selection method for hyperspectral image

Hyperspectral imaging makes it possible to obtain object information with fine spectral resolution as well as spatial resolution, which is beneficial to a wide array of applications. However, there is a high correlation among the bands in a hyperspectral image (HSI). Band selection (BS), selecting o...

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Bibliographic Details
Main Authors: Xuefeng Jiang, Lin Zhang, Junrui Liu, Shuying Li
Format: Article
Language:English
Published: Wiley 2019-03-01
Series:IET Computer Vision
Subjects:
pixel classification
orthogonal-projection-based algorithm
Euclidean sense
information-lossless compressed descriptor
orthogonal-projection BS method
efficient greedy-based unsupervised BS method
Online Access:https://doi.org/10.1049/iet-cvi.2018.5143

Internet

https://doi.org/10.1049/iet-cvi.2018.5143

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