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A Study on Rational Function Model Generation for TerraSAR-X Imagery

The Rational Function Model (RFM) has been widely used as an alternative to rigorous sensor models of high-resolution optical imagery in photogrammetry and remote sensing geometric processing. However, not much work has been done to evaluate the applicability of the RF model for Synthetic Aperture R...

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Autores principales: Eftekhari, Akram, Saadatseresht, Mohammad, Motagh, Mahdi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3821330/
https://www.ncbi.nlm.nih.gov/pubmed/24021971
http://dx.doi.org/10.3390/s130912030
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author Eftekhari, Akram
Saadatseresht, Mohammad
Motagh, Mahdi
author_facet Eftekhari, Akram
Saadatseresht, Mohammad
Motagh, Mahdi
author_sort Eftekhari, Akram
collection PubMed
description The Rational Function Model (RFM) has been widely used as an alternative to rigorous sensor models of high-resolution optical imagery in photogrammetry and remote sensing geometric processing. However, not much work has been done to evaluate the applicability of the RF model for Synthetic Aperture Radar (SAR) image processing. This paper investigates how to generate a Rational Polynomial Coefficient (RPC) for high-resolution TerraSAR-X imagery using an independent approach. The experimental results demonstrate that the RFM obtained using the independent approach fits the Range-Doppler physical sensor model with an accuracy of greater than 10(−3) pixel. Because independent RPCs indicate absolute errors in geolocation, two methods can be used to improve the geometric accuracy of the RFM. In the first method, Ground Control Points (GCPs) are used to update SAR sensor orientation parameters, and the RPCs are calculated using the updated parameters. Our experiment demonstrates that by using three control points in the corners of the image, an accuracy of 0.69 pixels in range and 0.88 pixels in the azimuth direction is achieved. For the second method, we tested the use of an affine model for refining RPCs. In this case, by applying four GCPs in the corners of the image, the accuracy reached 0.75 pixels in range and 0.82 pixels in the azimuth direction.
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spelling pubmed-38213302013-11-09 A Study on Rational Function Model Generation for TerraSAR-X Imagery Eftekhari, Akram Saadatseresht, Mohammad Motagh, Mahdi Sensors (Basel) Article The Rational Function Model (RFM) has been widely used as an alternative to rigorous sensor models of high-resolution optical imagery in photogrammetry and remote sensing geometric processing. However, not much work has been done to evaluate the applicability of the RF model for Synthetic Aperture Radar (SAR) image processing. This paper investigates how to generate a Rational Polynomial Coefficient (RPC) for high-resolution TerraSAR-X imagery using an independent approach. The experimental results demonstrate that the RFM obtained using the independent approach fits the Range-Doppler physical sensor model with an accuracy of greater than 10(−3) pixel. Because independent RPCs indicate absolute errors in geolocation, two methods can be used to improve the geometric accuracy of the RFM. In the first method, Ground Control Points (GCPs) are used to update SAR sensor orientation parameters, and the RPCs are calculated using the updated parameters. Our experiment demonstrates that by using three control points in the corners of the image, an accuracy of 0.69 pixels in range and 0.88 pixels in the azimuth direction is achieved. For the second method, we tested the use of an affine model for refining RPCs. In this case, by applying four GCPs in the corners of the image, the accuracy reached 0.75 pixels in range and 0.82 pixels in the azimuth direction. MDPI 2013-09-09 /pmc/articles/PMC3821330/ /pubmed/24021971 http://dx.doi.org/10.3390/s130912030 Text en © 2013 by the authors; licensee MDPI, 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 Article
Eftekhari, Akram
Saadatseresht, Mohammad
Motagh, Mahdi
A Study on Rational Function Model Generation for TerraSAR-X Imagery
title A Study on Rational Function Model Generation for TerraSAR-X Imagery
title_full A Study on Rational Function Model Generation for TerraSAR-X Imagery
title_fullStr A Study on Rational Function Model Generation for TerraSAR-X Imagery
title_full_unstemmed A Study on Rational Function Model Generation for TerraSAR-X Imagery
title_short A Study on Rational Function Model Generation for TerraSAR-X Imagery
title_sort study on rational function model generation for terrasar-x imagery
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3821330/
https://www.ncbi.nlm.nih.gov/pubmed/24021971
http://dx.doi.org/10.3390/s130912030
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