Document Type : Research Article


Department of Electronics & Instrumentation Engineering, Annamalai University, Chidambaram, India


The unsupervised learning method is one of the formidable operations in Hyper-Spectral Image (HSI) processing. Fuzzy C-Means (FCM) clustering is an optimistic and strategic method for selecting the unsupervised bands. There are some limits and standards in fuzzy clustering technique. The Glowworm Swarm Optimization (GSO) is proposed with combining fuzzy clustering and GSO. The GSO is introduced to enhance the performance of fuzzy clustering to optimize the characteristics of hyperspectral images. The main objective of the proposed method is to improve the accuracy of the hyperspectral datasets and to achieve it through better computational time. The experimental results are achieved through MATLAB toolbox and the proposed method has the capability to perform with the high quality hyperspectral image classification. Copyright © VBRI Press.

1.Yuen,PWT; Richardson,M.; The Imaging Science Journal,
2010, 058.

2.Gustavo Camps-Valls;Devis Tuia;Lorenzo Bruzzone; J ́on Atli
IEEE Signal Processing Magazine, 2014, 31.
3.Rajinikanth C.; Abraham S., Lincon; Journal of Advanced
Research in Dynamical & Control Systems, 2018, 10.

4.Nasser M. Nasrabadi;IEEE Signal Processing Magazine,2014.

5.Mingyang Zhang;Jingjing Ma;Maoguo Gong;IEEE Geoscience
and Remote Sensing Letters,2017.

6.Rajinikanth C.; Abraham Lincon S.; Journal of Advanced
Research in Dynamical & Control Systems, 2018, 10.