#5464. Fuzzy C-means technique for band reduction and segmentation of hyperspectral satellite image

August 2026publication date
Proposal available till 19-05-2025
4 total number of authors per manuscript0 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Computational Theory and Mathematics;
Theoretical Computer Science;
Software;
Artificial Intelligence;
Places in the authors’ list:
place 1place 2place 3place 4
FreeFreeFreeFree
2350 $1200 $1050 $900 $
Contract №5464.1 Contract №5464.2 Contract №5464.3 Contract №5464.4
1 place - free (for sale)
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)

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. Copyright
Keywords:
Centroid; Cluster; De-Correlation; Fuzzy C-Mean; K-Means

Contacts :
0