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Image Fusion in Remote Sensing Applications: A Review

by Vaibhav R. Pandit, R. J. Bhiwani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 120 - Number 10
Year of Publication: 2015
Authors: Vaibhav R. Pandit, R. J. Bhiwani
10.5120/21263-3846

Vaibhav R. Pandit, R. J. Bhiwani . Image Fusion in Remote Sensing Applications: A Review. International Journal of Computer Applications. 120, 10 ( June 2015), 22-32. DOI=10.5120/21263-3846

@article{ 10.5120/21263-3846,
author = { Vaibhav R. Pandit, R. J. Bhiwani },
title = { Image Fusion in Remote Sensing Applications: A Review },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 120 },
number = { 10 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 22-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume120/number10/21263-3846/ },
doi = { 10.5120/21263-3846 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:05:51.878749+05:30
%A Vaibhav R. Pandit
%A R. J. Bhiwani
%T Image Fusion in Remote Sensing Applications: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 10
%P 22-32
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Major technical constraints like minimum data storage at satellite platform in space, less bandwidth for communication with earth station, etc. limits the satellite sensors from capturing images with high spatial and high spectral resolutions simultaneously. To overcome this limitation, image fusion has proved to be a potential tool in remote sensing applications which integrates the information from combinations of panchromatic, multispectral or hyperspectral images; intended to result in a composite image having both higher spatial and higher spectral resolutions. The research in this area cites date back to last few decades, but the diverse approaches proposed so far by different researchers have been rarely discussed at one place. This paper is an honest attempt to collectively discuss all possible algorithms along with quality metrics following two assessment procedures i. e. at full and reduced scale resolutions to evaluate performance of these algorithms.

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Index Terms

Computer Science
Information Sciences

Keywords

Image fusion Relative spectral contribution methods Component substitution Multiresolution analysis Quality metrics for performance evaluation.

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