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Classification and Segmentation Models for Hyperspectral Imaging - An Overview

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Intelligent Technologies and Applications (INTAP 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1382))

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Abstract

An advancement in Hyperspectral Imaging (HI) technology is creating important attraction among the researchers to develop better classification techniques. This technology is well known for its high spatial and spectral information due to which the discrimination of materials is much more accurate and efficient. The useful information is extracted in Hyperspectral Imaging technology after applying it in agriculture, biomedical, and disaster management studies. A review comparison has been carried out for air borne images using hyperspectral acquisition hardware for classification as well as segmentation purpose. Numerous approaches that have been focused for implementation namely semi-supervised technique used for hyperspectral imaging using active learning and multinomial logistic regression, Generalized Composite Kernels (GCKs) classification framework, classification of spectral-spatial based data on loopy belief propagation (LBP), multiple feature learning of HI classification, and semi-supervised GCKs with classification accuracy on AVIRIS dataset (59.97%, 92.89%, 81.45%, 75.84%, and 95.50) and segmentation accuracies using α-expansion method as (73.27%, 93.57%, 92.86%, 91.73% and 98.31), respectively.

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Author information

Authors and Affiliations

  1. Pakistan Institute of Engineering & Applied Sciences (PIEAS), Nilore, Islamabad, 45650, Pakistan

    Syed Taimoor Hussain Shah & Shahzad Ahmad Qureshi

  2. National Institute of Lasers and Optronics (NILOP) College, PIEAS, Nilore, Islamabad, 45650, Pakistan

    Aziz ul Rehman

  3. Comsats University, Wah Cantt, Pakistan

    Syed Adil Hussain Shah

  4. Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, Pakistan

    Jamal Hussain

Authors
  1. Syed Taimoor Hussain Shah
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  2. Shahzad Ahmad Qureshi
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  3. Aziz ul Rehman
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  4. Syed Adil Hussain Shah
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  5. Jamal Hussain
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Correspondence to Shahzad Ahmad Qureshi .

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Editors and Affiliations

  1. NTNU, Gjøvik, Norway

    Sule Yildirim Yayilgan

  2. The Islamia University of Bahawalpur, Punjab, Pakistan

    Imran Sarwar Bajwa

  3. University of Agder, Kristiansand, Norway

    Filippo Sanfilippo

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Shah, S.T.H., Qureshi, S.A., Rehman, A.u., Shah, S.A.H., Hussain, J. (2021). Classification and Segmentation Models for Hyperspectral Imaging - An Overview. In: Yildirim Yayilgan, S., Bajwa, I.S., Sanfilippo, F. (eds) Intelligent Technologies and Applications. INTAP 2020. Communications in Computer and Information Science, vol 1382. Springer, Cham. https://doi.org/10.1007/978-3-030-71711-7_1

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  • DOI: https://doi.org/10.1007/978-3-030-71711-7_1

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