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A Novel Equilibrium Optimization Technique for Band Selection of Hyperspectral Images

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Computational Intelligence in Communications and Business Analytics (CICBA 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1406))

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Abstract

Band selection of hyperspectral images is a rising research area. Because of the shortage of the labeled information set of hyperspectral imagery, it is additionally challenging task. Band selection problem can be seen as a two-way problem i.e. optimization of the number of chosen bands as well as optimization of the chosen bands itself. In this article, a novel strategy primarily based on Equilibrium Optimization (EO) is proposed. The Equilibrium Law of any object acts as the motivation in favour of this method. This technique suggests a persuasive result in assessment with other popular methods like MI (Mutual Information), WaLuDi (Wards linkage strategy using divergence), TMI (Trivariate MI), ACO (Ant Colony Optimization), and DE (Differential Evolution) for different datasets like Botswana, KSC, etc.

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Author information

Authors and Affiliations

  1. Women’s Polytechnic, Kolkata, India

    Aditi Roy Chowdhury

  2. Heritage Institute of Technology, Kolkata, India

    Joydev Hazra

  3. Kalyani Government Engineering College, Kalyani, Nadia, India

    Kousik Dasgupta

  4. Visvabharati University, Santiniketan, India

    Paramartha Dutta

Authors
  1. Aditi Roy Chowdhury
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  2. Joydev Hazra
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  3. Kousik Dasgupta
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  4. Paramartha Dutta
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Editor information

Editors and Affiliations

  1. Visva-Bharati University, Santiniketan, India

    Paramartha Dutta

  2. University of Kalyani, Kalyani, India

    Jyotsna K. Mandal

  3. Assam University, Silchar, India

    Somnath Mukhopadhyay

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Chowdhury, A.R., Hazra, J., Dasgupta, K., Dutta, P. (2021). A Novel Equilibrium Optimization Technique for Band Selection of Hyperspectral Images. In: Dutta, P., Mandal, J.K., Mukhopadhyay, S. (eds) Computational Intelligence in Communications and Business Analytics. CICBA 2021. Communications in Computer and Information Science, vol 1406. Springer, Cham. https://doi.org/10.1007/978-3-030-75529-4_7

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  • DOI: https://doi.org/10.1007/978-3-030-75529-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-75528-7

  • Online ISBN: 978-3-030-75529-4

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