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Biblioteca Spectral similarity-preserving hyperspectral band selection

Spectral similarity-preserving hyperspectral band selection

Spectral similarity-preserving hyperspectral band selection

Resource information

Date of publication
Dezembro 2013
Resource Language
ISBN / Resource ID
AGRIS:US201600057396
Pages
969-978

Due to the high spectral resolution, hyperspectral images (HSI) have been widely used in land cover classification and material identification. Band selection is one of the necessary preprocessings to reduce the data volume and the redundancy therein for the subsequent analysis. Aiming at speeding up the search-based band selection process, this letter proposes a new technique from the perspective of spectral curve shape similarity. Through a newly defined measure for band subset discriminativeness (BSD), class-specific important bands (IBs) are retained which can preserve the spectral similarity of the samples from the same class and narrow down candidate band subset for the following search procedure. Then optimal search is performed in the aggregated band subset from all classes. Experiments on the Indian Pine benchmark data set have proved the efficiency and effectiveness of the proposed method.

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Authors and Publishers

Author(s), editor(s), contributor(s)

Li, Shijin
Zhu, Yuelong
Wan, Dingsheng
Feng, Jun

Publisher(s)
Data Provider