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An Operational Tool for the Automatic Detection and Removal of Border Noise in Sentinel-1 GRD Products
The presence of border noise in Sentinel-1 Ground Range Detected (GRD) products is an undesired processing artifact that limits their full exploitation in a number of applications. All of the Sentinel-1 GRD products generated before March 2018—more than 800,000—are affected by this particular type o...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6209976/ https://www.ncbi.nlm.nih.gov/pubmed/30322211 http://dx.doi.org/10.3390/s18103454 |
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author | Stasolla, Mattia Neyt, Xavier |
author_facet | Stasolla, Mattia Neyt, Xavier |
author_sort | Stasolla, Mattia |
collection | PubMed |
description | The presence of border noise in Sentinel-1 Ground Range Detected (GRD) products is an undesired processing artifact that limits their full exploitation in a number of applications. All of the Sentinel-1 GRD products generated before March 2018—more than 800,000—are affected by this particular type of noise. In March 2018, an official fix was deployed that solved the problem for a large portion of the newly generated products, but it did not cover the entire range of products, hence the need for an operational tool that is able to effectively and consistently remove border noise in an automated way. Currently, a few solutions have been proposed that try to address the problem, but all of them have limitations. The scope of this paper is therefore to present a new method based on mathematical morphology for the automatic detection and masking of border noise in Sentinel-1 GRD products that is able to overcome the existing limitations. To evaluate the performance of the method, a detailed numerical assessment was carried out, using, as a benchmark, the ‘Remove GRD Border Noise’ module integrated in ESA’s Sentinel Application Platform. The results showed that the proposed method is capable of very accurately removing the undesired noisy pixels from GRD images, regardless of their acquisition mode, polarization, or resolution and can cope with challenging features within the image scenes that typically affect other approaches. |
format | Online Article Text |
id | pubmed-6209976 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-62099762018-11-02 An Operational Tool for the Automatic Detection and Removal of Border Noise in Sentinel-1 GRD Products Stasolla, Mattia Neyt, Xavier Sensors (Basel) Article The presence of border noise in Sentinel-1 Ground Range Detected (GRD) products is an undesired processing artifact that limits their full exploitation in a number of applications. All of the Sentinel-1 GRD products generated before March 2018—more than 800,000—are affected by this particular type of noise. In March 2018, an official fix was deployed that solved the problem for a large portion of the newly generated products, but it did not cover the entire range of products, hence the need for an operational tool that is able to effectively and consistently remove border noise in an automated way. Currently, a few solutions have been proposed that try to address the problem, but all of them have limitations. The scope of this paper is therefore to present a new method based on mathematical morphology for the automatic detection and masking of border noise in Sentinel-1 GRD products that is able to overcome the existing limitations. To evaluate the performance of the method, a detailed numerical assessment was carried out, using, as a benchmark, the ‘Remove GRD Border Noise’ module integrated in ESA’s Sentinel Application Platform. The results showed that the proposed method is capable of very accurately removing the undesired noisy pixels from GRD images, regardless of their acquisition mode, polarization, or resolution and can cope with challenging features within the image scenes that typically affect other approaches. MDPI 2018-10-14 /pmc/articles/PMC6209976/ /pubmed/30322211 http://dx.doi.org/10.3390/s18103454 Text en © 2018 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Stasolla, Mattia Neyt, Xavier An Operational Tool for the Automatic Detection and Removal of Border Noise in Sentinel-1 GRD Products |
title | An Operational Tool for the Automatic Detection and Removal of Border Noise in Sentinel-1 GRD Products |
title_full | An Operational Tool for the Automatic Detection and Removal of Border Noise in Sentinel-1 GRD Products |
title_fullStr | An Operational Tool for the Automatic Detection and Removal of Border Noise in Sentinel-1 GRD Products |
title_full_unstemmed | An Operational Tool for the Automatic Detection and Removal of Border Noise in Sentinel-1 GRD Products |
title_short | An Operational Tool for the Automatic Detection and Removal of Border Noise in Sentinel-1 GRD Products |
title_sort | operational tool for the automatic detection and removal of border noise in sentinel-1 grd products |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6209976/ https://www.ncbi.nlm.nih.gov/pubmed/30322211 http://dx.doi.org/10.3390/s18103454 |
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