Abstract
In remote sensing, spectral band selection has been a primordial step to improve the classification of hyperspectral images. It aims at finding the most important information from a set of bands by eliminating the irrelevant, noisy, and highly correlated bands. In this paper, the band selection problem is regarded as a combinatorial optimization problem. We propose a new band selection approach for hyperspectral image classification based on the Gray Wolf Optimizer (GWO) which is a new meta-heuristic that simulate the hunting process of gray wolf in nature. A new binary version of GWO based on transfer function is proposed. In addition, a new fitness function is designed using two terms: the first term is the SVM classifier and the second term of the fitness function is SNR measure (Signal to Noise Ration) which measures the capacity of discrimination. The proposed approach is benchmarked on three hyperspectral images widely used in band selection and hyperspectral images classification. The experimental results show that this approach is suitable to the challenging problem of spectral band selection and provides a higher classification accuracy rate compared to the other band selection methods.
The original version of this chapter has been revised. The author “Mohammed Ouali’s affiliation has been updated. The correction to this chapter can be found at https://doi.org/10.1007/978-3-030-05481-6_26
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Change history
16 April 2023
In the original version of the book, the following belated corrections has been updated: In chapter “Spectral Band Selection Using Binary Gray Wolf Optimizer and Signal to Noise Ration Measure”, the affiliation “Thales Canada Inc., 105 Moatfield Drive, North York, ON, M3B 0A4, Canada and Computer Science Department, University of Sherbrooke, Sherbrooke, QC, J1K2R1, Canada” of author “Mohammed Ouali” is to be changed to “Thales Canada Inc., 105 Moatfield Drive, North York, ON, M3B 0A4, Canada”.
The correction chapter and the book have been updated with the change.
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Medjahed, S.A., Ouali, M. (2019). Spectral Band Selection Using Binary Gray Wolf Optimizer and Signal to Noise Ration Measure. In: Chikhi, S., Amine, A., Chaoui, A., Saidouni, D.E. (eds) Modelling and Implementation of Complex Systems. MISC 2018. Lecture Notes in Networks and Systems, vol 64. Springer, Cham. https://doi.org/10.1007/978-3-030-05481-6_6
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