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A Novel Local Consensus Inspired Spatial Fuzzy Method for Classification and Spectral Unmixing of Hyperspectral Data

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Proceedings of the International Conference on Computing and Communication Systems

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 170))

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Abstract

In this paper, a novel local consensus inspired spatial fuzzy method has been introduced to perform classification and spectral unmixing of hyperspectral image pixels. Here, a local consensus index inspired spatial membership has been combined with the global membership to deal with non-homogeneity and noise present in the hyperspectral image scene. The modified membership function has been used to produce the fractional abundance for end members present in the considered image scene, which serves the purpose of spectral unmixing. To analyze the superiority of the proposed method, partition coefficient and partition entropy of the proposed method have been thoroughly compared with the fuzzy-based state of the art methods and some recently published novel works. The qualitative result and fractional abundance are observed and thoroughly analyzed.

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Authors and Affiliations

  1. RCC Institute of Information Technology, Kolkata, India

    Srirupa Das

  2. Maulana Abul Kalam Azad University of Technology, Haringhata, West Bengal, India

    Somdatta Chakravortty

Authors
  1. Srirupa Das
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  2. Somdatta Chakravortty
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Corresponding author

Correspondence to Somdatta Chakravortty .

Editor information

Editors and Affiliations

  1. Department of Information Technology, North-Eastern Hill University, Shillong, Meghalaya, India

    Arnab Kumar Maji

  2. Department of Information Technology, North-Eastern Hill University, Shillong, Meghalaya, India

    Goutam Saha

  3. Department of Information Technology, North-Eastern Hill University, Shillong, Meghalaya, India

    Sufal Das

  4. Department of Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal, India

    Subhadip Basu

  5. Departamento de Engenharia Mecânica, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

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Das, S., Chakravortty, S. (2021). A Novel Local Consensus Inspired Spatial Fuzzy Method for Classification and Spectral Unmixing of Hyperspectral Data. In: Maji, A.K., Saha, G., Das, S., Basu, S., Tavares, J.M.R.S. (eds) Proceedings of the International Conference on Computing and Communication Systems. Lecture Notes in Networks and Systems, vol 170. Springer, Singapore. https://doi.org/10.1007/978-981-33-4084-8_13

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