IDEAS home Printed from https://ideas.repec.org/a/igg/jfsa00/v10y2021i4p79-100.html
   My bibliography  Save this article

Fuzzy C-Means Technique for Band Reduction and Segmentation of Hyperspectral Satellite Image

Author

Listed:
  • Saravanakumar V.

    (SreeNidhi Institute of Science and Technology, Hyderabad, India)

  • Kavitha M. Saravanan

    (Manonmaniam Sundaranar University, India)

  • Balaram V. V. S. S. S.

    (Sreenidhi Institute of Science and Technology, India)

  • Anantha Sivaprakasam S.

    (GVN College, India)

Abstract

This paper put forward for the segmentation process on the hyperspectral remote sensing satellite scene. The prevailing algorithm, fuzzy c-means, is performed on this scene. Moreover, this algorithm is performed in both inter band as well as intra band clustering (i.e., band reduction and segmentation are performed by this algorithm). Furthermore, a band that has topmost variance is selected from every cluster. This structure diminishes these bands into three bands. This reduced band is de-correlated, and subsequently segmentation is carried out using this fuzzy algorithm.

Suggested Citation

  • Saravanakumar V. & Kavitha M. Saravanan & Balaram V. V. S. S. S. & Anantha Sivaprakasam S., 2021. "Fuzzy C-Means Technique for Band Reduction and Segmentation of Hyperspectral Satellite Image," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 10(4), pages 79-100, October.
    • Handle: RePEc:igg:jfsa00:v:10:y:2021:i:4:p:79-100
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJFSA.2021100105
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jfsa00:v:10:y:2021:i:4:p:79-100. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.