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Statistical Modeling of SAR Images: A Survey
Statistical modeling is essential to SAR (Synthetic Aperture Radar) image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of ter...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Molecular Diversity Preservation International (MDPI)
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3270869/ https://www.ncbi.nlm.nih.gov/pubmed/22315568 http://dx.doi.org/10.3390/s100100775 |
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author | Gao, Gui |
author_facet | Gao, Gui |
author_sort | Gao, Gui |
collection | PubMed |
description | Statistical modeling is essential to SAR (Synthetic Aperture Radar) image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of terrain scattering mechanism, which helps to develop algorithms for effective image interpretation and creditable image simulation. Numerous statistical models have been developed to describe SAR image data, and the purpose of this paper is to categorize and evaluate these models. We first summarize the development history and the current researching state of statistical modeling, then different SAR image models developed from the product model are mainly discussed in detail. Relevant issues are also discussed. Several promising directions for future research are concluded at last. |
format | Online Article Text |
id | pubmed-3270869 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-32708692012-02-07 Statistical Modeling of SAR Images: A Survey Gao, Gui Sensors (Basel) Review Statistical modeling is essential to SAR (Synthetic Aperture Radar) image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of terrain scattering mechanism, which helps to develop algorithms for effective image interpretation and creditable image simulation. Numerous statistical models have been developed to describe SAR image data, and the purpose of this paper is to categorize and evaluate these models. We first summarize the development history and the current researching state of statistical modeling, then different SAR image models developed from the product model are mainly discussed in detail. Relevant issues are also discussed. Several promising directions for future research are concluded at last. Molecular Diversity Preservation International (MDPI) 2010-01-21 /pmc/articles/PMC3270869/ /pubmed/22315568 http://dx.doi.org/10.3390/s100100775 Text en ©2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/) |
spellingShingle | Review Gao, Gui Statistical Modeling of SAR Images: A Survey |
title | Statistical Modeling of SAR Images: A Survey |
title_full | Statistical Modeling of SAR Images: A Survey |
title_fullStr | Statistical Modeling of SAR Images: A Survey |
title_full_unstemmed | Statistical Modeling of SAR Images: A Survey |
title_short | Statistical Modeling of SAR Images: A Survey |
title_sort | statistical modeling of sar images: a survey |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3270869/ https://www.ncbi.nlm.nih.gov/pubmed/22315568 http://dx.doi.org/10.3390/s100100775 |
work_keys_str_mv | AT gaogui statisticalmodelingofsarimagesasurvey |