An unsupevised package for multi-spectral image processing for remote data

Zaid, Muhsin A. and Zeki, Akram M. (2015) An unsupevised package for multi-spectral image processing for remote data. Journal of Advanced Computer Science and Technology Research (JACSTR), 5 (4). pp. 113-122. ISSN 2231-8852

PDF - Published Version Restricted to Repository staff only Download (692kB) | Request a copy

Abstract

The ability to match digital images and technique combination in the computer world had revolutionalised the trend. This paper researched on the unsupervised classification of the Multi-Spectral Image. All the two classes under the unsupervised classification were presented and explained. That is the K-Means (KM) and Kohonen Neural Network (KNN). A package for Multi-Spectral Images is designed with the ability to read data, apply Principal Component Analysis (PCA) as a feature extraction, then apply False Colour Composite (FCC) as one of the classification techniques in multi-spectral images. The unsupervised classification method is considered throughout in this research.

Item Type:	Article (Journal)
Additional Information:	6153/49596
Uncontrolled Keywords:	Index - K-Means (KM), Kohenen Neural Network (KNN), Principal Component Analysis (PCA), False Colour Composite (FCC).
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User:	Akram M Zeki
Date Deposited:	13 Feb 2016 16:18
Last Modified:	16 Oct 2017 14:49
URI:	http://irep.iium.edu.my/id/eprint/49596

Actions (login required)

View Item