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

Saravanakumar V., Kavitha M. Saravanan, Balaram V. V. S. S. S. and Anantha Sivaprakasam S.
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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

International Journal of Fuzzy System Applications (IJFSA), 2021, vol. 10, issue 4, 79-100

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.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jfsa00:v:10:y:2021:i:4:p:79-100

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