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

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 th...

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Main Authors: Zaid, Muhsin A., Zeki, Akram M.
Format: Article
Language:English
Published: Design for Scientific Renaissance 2015
Subjects:
Online Access:http://irep.iium.edu.my/49596/
http://irep.iium.edu.my/49596/1/1249-2938-1-PB.pdf
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author Zaid, Muhsin A.
Zeki, Akram M.
author_facet Zaid, Muhsin A.
Zeki, Akram M.
author_sort Zaid, Muhsin A.
building IIUM Repository
collection Online Access
description 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.
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publishDate 2015
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spelling iium-495962017-10-16T06:49:55Z http://irep.iium.edu.my/49596/ An unsupevised package for multi-spectral image processing for remote data Zaid, Muhsin A. Zeki, Akram M. T Technology (General) 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. Design for Scientific Renaissance 2015-12 Article PeerReviewed application/pdf en http://irep.iium.edu.my/49596/1/1249-2938-1-PB.pdf 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 http://www.sign-ific-ance.co.uk/index.php/JACSTR/article/view/1249
spellingShingle T Technology (General)
Zaid, Muhsin A.
Zeki, Akram M.
An unsupevised package for multi-spectral image processing for remote data
title An unsupevised package for multi-spectral image processing for remote data
title_full An unsupevised package for multi-spectral image processing for remote data
title_fullStr An unsupevised package for multi-spectral image processing for remote data
title_full_unstemmed An unsupevised package for multi-spectral image processing for remote data
title_short An unsupevised package for multi-spectral image processing for remote data
title_sort unsupevised package for multi-spectral image processing for remote data
topic T Technology (General)
url http://irep.iium.edu.my/49596/
http://irep.iium.edu.my/49596/
http://irep.iium.edu.my/49596/1/1249-2938-1-PB.pdf