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Reseach Article

Fusion of Difference Images for Change detection

Published on December 2013 by Deepthy. R, A. Vasuki
International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences
Foundation of Computer Science USA
ICIIIOES - Number 6
December 2013
Authors: Deepthy. R, A. Vasuki
18c0d039-27d5-4e49-b21e-8b57d974dc2a

Deepthy. R, A. Vasuki . Fusion of Difference Images for Change detection. International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences. ICIIIOES, 6 (December 2013), 28-37.

@article{
author = { Deepthy. R, A. Vasuki },
title = { Fusion of Difference Images for Change detection },
journal = { International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences },
issue_date = { December 2013 },
volume = { ICIIIOES },
number = { 6 },
month = { December },
year = { 2013 },
issn = 0975-8887,
pages = { 28-37 },
numpages = 10,
url = { /proceedings/iciiioes/number6/14322-1571/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences
%A Deepthy. R
%A A. Vasuki
%T Fusion of Difference Images for Change detection
%J International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences
%@ 0975-8887
%V ICIIIOES
%N 6
%P 28-37
%D 2013
%I International Journal of Computer Applications
Abstract

The Land use/ Land cover change in urban areas and the difference of the earth surface after the flood can be detected from remote sensing images by performing image differencing algorithms. Although many algorithms were proposed to generate difference images, the results are inconsistent. In order to integrate the merits of difference algorithms, fusion techniques are used to merge multiple difference images. The image fusion algorithms applied here are based on Principal Component Analysis and Discrete Wavelet Transform. Principal Component Analysis is the unsupervised technique, the change is guaranteed to be preserved in the major component images. In Wavelet based method, image fusion is performed at the pixel level and the details from source images can be reserved at various scales. The algorithms are implemented on the satellite images and results are presented.

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Index Terms

Computer Science
Information Sciences

Keywords

Image Differencing Change Detection Image Fusion Principal Component Analysis Discrete Wavelet Transform.