Nature-inspired framework for hyperspectral band selection
Abstract
Although hyperspectral images acquired by on-board satellites provide information from a wide range of wavelengths in the spectrum, the obtained information is usually highly correlated. This paper proposes a novel framework to reduce the computation cost for large amounts of data based on the efficiency of the optimum-path forest (OPF) classifier and the power of metaheuristic algorithms to solve combinatorial optimizations. Simulations on two public data sets have shown that the proposed framework can indeed improve the effectiveness of the OPF and considerably reduce data storage costs.
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
Several other studies have focused on further improving the classification accuracy of hyperspectral data.
“Several other studies have focused on further improving the classification accuracy [14–16].”
From Development of online classification system for construction waste based on industrial camera and hyperspectral camera (2019) · cites this paper as [15]
Cited by
Sorted by citations
Xiao, W., Yang, J., Fang, H., Zhuang, J., & Ku, Y. (2019) · PLOS ONE · doi:10.1371/journal.pone.0208706 · Cited by 27 · see citing works
- Authors
- Nakamura, R. Y. M., Fonseca, L. M. G., Santos, J. A. D., Torres, R. D. S., Yang, X.-S., & Papa, J. P.
- Affiliations
- Universidade Estadual Paulista (Unesp) (BR)
- Universidade Estadual de Campinas (UNICAMP) (BR)
- Middlesex University London (GB)
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2014-04
- Volume
- 52
- Issue
- 4
- Pages
- 2126-2137
- ISSN
- 0196-2892 (ISSN-L)
- 1558-0644
- OpenAlex
- W2169709581
- Cited by
- 70
- References
- 0
- Citations by year
- 2025: 3 · 2024: 3 · 2023: 3 · 2022: 5 · 2021: 7 · 2020: 6 · 2019: 11 · 2018: 5 · 2017: 11 · 2016: 6 · 2015: 6 · 2014: 3 · 2013: 1
- FWCI
- 13.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Geoscience and Remote Sensing (publishedVersion)
- Acervo Digital da Universidade Estadual Paulista (Universidade Estadual Paulista) (submittedVersion)
- Middlesex University Research Repository (Middlesex University Of London) (submittedVersion)
- UNESP Institutional Repository (São Paulo State University) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Media Technology › Remote-Sensing Image Classification
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Keywords
- hyperspectral band selection, optimum-path forest, metaheuristic algorithms, combinatorial optimization, spectral redundancy, bio-inspired algorithms
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