3. Chinese Acad Sci, Innovat Acad Microsatellites, Shanghai, Peoples R China
折叠
Abstract
Selecting a subset of bands from hyperspectral data can improve the discrimination of ground targets because the most distinguishing spectral features are utilized. Targets with similar spectra are particularly challenging for band selection. A band selection method using the N-dimensional Solid Spectral Angle (NSSA) was recently proposed by Tian et al. (2016) to select the most dissimilar spectral regions amongst targets, but no case studies have been conducted using data from natural targets and there are currently no guidelines for the parameter selection in the NSSA band selection method. This study uses two spectral datasets of geologic relevance (clay minerals and ultramafic rocks), each with spectrally similar materials, to establish guidelines for the selection of two parameters (k and threshold) that will enable the use of the method for practical applications. K defines the band interval (relates to feature width) from which NSSA is calculated, and the threshold defines the number of bands selected from a profile of NSSA as a function of wavelength. The first guideline consists in constraining the maximum k value based on the spectral dimensionality of the widest significant spectral feature for the materials under study. The second guideline is to use a profile of the NSSA value as a function of wavelength for each permissible k value to capture the primary wavelength regions of high NSSA values. Finally, the threshold parameter for each k is estimated from a graph of the NSSA value as a function of the number of bands. The guidelines on the parameter definition allow non-expert users to select a subset of bands while capturing both narrow and broad discriminating features.
Key words
Hyperspectral band selection/Spectral similarity/Target discrimination
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出版年
2019
International journal of applied earth observation and geoinformation
NSTL
Elsevier