Quality assessment of restored satellite data based on signal to noise ratio

Abstract

A practical concept of assessing the quality of restored data based on signal to noise ratio (SNR) is reported. The data come from remote sensing satellite and has undergone restoration process due to atmospheric haze effects. The restoration involves removing haze mean due to haze scattering and haze randomness due to haze spatial variability. The results shows that the SNR of restored data can be computed if the haze mean and haze randomness components are known.

Metadata

Item Type:	Article
Authors/Creators:	Ahmad, A. Quegan, S.
Copyright, Publisher and Additional Information:	© 2016 Asmala Ahmad and Shaun Quegan. This article is distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords:	Haze; Remote Sensing; Signal to Noise ratio
Dates:	Published: 28 July 2016 Published (online): 28 July 2016
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield)
Depositing User:	Symplectic Sheffield
Date Deposited:	11 Apr 2017 13:34
Last Modified:	11 Apr 2017 13:34
Published Version:	http://doi.org/10.12988/ams.2016.64148
Status:	Published
Publisher:	Hikari
Refereed:	Yes
Identification Number:	10.12988/ams.2016.64148
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:114919

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Quality assessment of restored satellite data based on signal to noise ratio

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