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Optimal Band Selection Using Generalized Covering-Based Rough Sets on Hyperspectral Remote Sensing Big Data

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Advances in Big Data and Cloud Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 750))

Abstract

Hyperspectral remote sensing has been gaining attention from the past few decades. Due to the diverse and high dimensionality nature of the remote sensing data, it is called as remote sensing Big Data. Hyperspectral images have high dimensionality due to number of spectral bands and pixels having continuous spectrum. These images provide us with more details than other images but still, it suffers from ‘curse of dimensionality’. Band selection is the conventional method to reduce the dimensionality and remove the redundant bands. Many methods have been developed in the past years to find the optimal set of bands. Generalized covering-based rough set is an extended method of rough sets in which indiscernibility relations of rough sets are replaced by coverings. Recently, this method is used for attribute reduction in pattern recognition and data mining. In this paper, we will discuss the implementation of covering-based rough sets for optimal band selection of hyperspectral images and compare these results with the existing methods like PCA, SVD and rough sets.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Karnataka, Surathkal, India

    Harika Kelam

  2. Faculty of Computer Science and Engineering Department, National Institute of Technology Karnataka, Surathkal, India

    M. Venkatesan

Authors
  1. Harika Kelam
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  2. M. Venkatesan
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Corresponding author

Correspondence to Harika Kelam .

Editor information

Editors and Affiliations

  1. Department of Computer Sciences Technology, Karunya Institute of Technology & Sciences, Coimbatore, Tamil Nadu, India

    J. Dinesh Peter

  2. Department of Civil and Environmental Engineering, University of Missouri, Columbia, MO, USA

    Amir H. Alavi

  3. School of Computing, Engineering and Mathematics, University of Western Sydney, Sydney, NSW, Australia

    Bahman Javadi

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Kelam, H., Venkatesan, M. (2019). Optimal Band Selection Using Generalized Covering-Based Rough Sets on Hyperspectral Remote Sensing Big Data. In: Peter, J., Alavi, A., Javadi, B. (eds) Advances in Big Data and Cloud Computing. Advances in Intelligent Systems and Computing, vol 750. Springer, Singapore. https://doi.org/10.1007/978-981-13-1882-5_24

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