Hyperspectral band selection using crossover based gravitational search algorithm
Zabalza, Jaime and Zhang, Aizhu and Ma, Ping and Liu, Sihan and Sun, Genyun and Huang, Hui and Wang, Zhenjie and Lin, Chengyan (2018) Hyperspectral band selection using crossover based gravitational search algorithm. IET Image Processing. ISSN 1751-9659 (https://doi.org/10.1049/iet-ipr.2018.5362)
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Abstract
Band selection is an important data dimensionality reduction tool in hyperspectral images (HSIs). To identify the most informative subset band from the hundreds of highly corrected bands in HSIs, a novel hyperspectral band selection method using a crossover based gravitational search algorithm (CGSA) is presented in this paper. In this method, the discriminative capability of each band subset is evaluated by a combined optimization criterion, which is constructed based on the overall classification accuracy and the size of the band subset. As the evolution of the criterion, the subset is updated using the V-shaped transfer function based CGSA. Ultimately, the band subset with the best fitness value is selected. Experiments on two public hyperspectral datasets, i.e. the Indian Pines dataset and the Pavia University dataset, have been conducted to test the performance of the proposed method. Comparing experimental results against the basic GSA and the PSOGSA (hybrid PSO and GSA) revealed that all of the three GSA variants can considerably reduce the band dimensionality of HSIs without damaging their classification accuracy. Moreover, the CGSA shows superiority on both the effectiveness and efficiency compared to the other two GSA variants.
ORCID iDs
Zabalza, Jaime ORCID: https://orcid.org/0000-0002-0634-1725, Zhang, Aizhu, Ma, Ping, Liu, Sihan, Sun, Genyun, Huang, Hui, Wang, Zhenjie and Lin, Chengyan;-
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Item type: Article ID code: 65301 Dates: DateEvent17 August 2018Published17 August 2018Published Online25 June 2018AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 29 Aug 2018 11:37 Last modified: 25 Nov 2024 01:15 URI: https://strathprints.strath.ac.uk/id/eprint/65301