Multi spectral image classification using cluster ensemble technique
by K. Radhika; S. Varadarajan; Y. Muralimohanbabu
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 17, No. 1/2, 2018

Abstract: Satellite image classification is an imperative system utilised as a part of remote sensing. Primary data of extraordinary significance to different difficulties can be acquired straightforwardly from Land-cover observation. Different information partitions inferred by various clustering methods can be gathered into a new solution by cluster ensembles. Supervised iterative expectation-maximisation (EM) method can be initialised by cluster ensemble based strategy which will be examined in the paper. The performance of clustering of the proposed method is compared with individual clustering of the ensemble for medium resolution and a very high spatial resolution images. The accuracy measurements have done with different test points. The state of art techniques are giving less accuracy and are not well defined. This paper will explore the possibility of all accuracy parameters with supervised classification results. The accuracy parameters are well tested and compared in this paper with various start of art techniques.

Online publication date: Tue, 08-May-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Systems Technologies and Applications (IJISTA):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email