{"title":"The performance of speckle filters on Copernicus Sentinel-1 SAR images containing natural oil slicks","authors":"C. Vrinceanu, S. Grebby, S. Marsh","doi":"10.1144/qjegh2022-046","DOIUrl":null,"url":null,"abstract":"Synthetic Aperture Radar (SAR) is traditionally used in the identification, mapping, and analysis of petroleum slicks, regardless of their origin. On SAR images, oil slicks appear as dark patches that contrast with the brightness of the surrounding sea surface. This distinction allows for automated detection algorithms to be designed using computer vision methods for objective oil slick identification. Nevertheless, efficient interpretation of the SAR imagery by statistical analysis can be diminished due to the speckle effect present on SAR images, a granular artefact associated with the coherent nature of SAR, which visually degrades the image quality. In this study, a quantitative and qualitative assessment of common SAR image despeckling methods is presented, analyzing their performance when applied to images containing natural oil slicks. The assessment is performed on Copernicus Sentinel-1 images acquired with various temporal and environmental conditions. The assessment covers a diverse area of filters that employ Bayesian and non-linear statistics in the spatial, transform and wavelet domains, focusing on their demonstrated performance and capabilities for edge and texture retention. In summary, the results reveal that filters using local statistics in the spatial domain produce consistent desired effects. The novel SAR-BM3D algorithm can be used effectively, albeit with a higher computational demand.\n \n Supplementary material:\n Implementations of the speckle filters used in this paper are made available at:\n https://github.com/cavrinceanu/specklefilters\n under an MIT license. Image statistics data is available for Tables 3-11 at:\n https://doi.org/10.6084/m9.figshare.13010405\n \n \n Thematic collection:\n This article is part of the Remote sensing for site investigations on Earth and other planets collection available at:\n https://www.lyellcollection.org/cc/remote-sensing-for-site-investigations-on-earth-and-other-planets\n","PeriodicalId":20937,"journal":{"name":"Quarterly Journal of Engineering Geology and Hydrogeology","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quarterly Journal of Engineering Geology and Hydrogeology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1144/qjegh2022-046","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, GEOLOGICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Synthetic Aperture Radar (SAR) is traditionally used in the identification, mapping, and analysis of petroleum slicks, regardless of their origin. On SAR images, oil slicks appear as dark patches that contrast with the brightness of the surrounding sea surface. This distinction allows for automated detection algorithms to be designed using computer vision methods for objective oil slick identification. Nevertheless, efficient interpretation of the SAR imagery by statistical analysis can be diminished due to the speckle effect present on SAR images, a granular artefact associated with the coherent nature of SAR, which visually degrades the image quality. In this study, a quantitative and qualitative assessment of common SAR image despeckling methods is presented, analyzing their performance when applied to images containing natural oil slicks. The assessment is performed on Copernicus Sentinel-1 images acquired with various temporal and environmental conditions. The assessment covers a diverse area of filters that employ Bayesian and non-linear statistics in the spatial, transform and wavelet domains, focusing on their demonstrated performance and capabilities for edge and texture retention. In summary, the results reveal that filters using local statistics in the spatial domain produce consistent desired effects. The novel SAR-BM3D algorithm can be used effectively, albeit with a higher computational demand.
Supplementary material:
Implementations of the speckle filters used in this paper are made available at:
https://github.com/cavrinceanu/specklefilters
under an MIT license. Image statistics data is available for Tables 3-11 at:
https://doi.org/10.6084/m9.figshare.13010405
Thematic collection:
This article is part of the Remote sensing for site investigations on Earth and other planets collection available at:
https://www.lyellcollection.org/cc/remote-sensing-for-site-investigations-on-earth-and-other-planets
期刊介绍:
Quarterly Journal of Engineering Geology and Hydrogeology is owned by the Geological Society of London and published by the Geological Society Publishing House.
Quarterly Journal of Engineering Geology & Hydrogeology (QJEGH) is an established peer reviewed international journal featuring papers on geology as applied to civil engineering mining practice and water resources. Papers are invited from, and about, all areas of the world on engineering geology and hydrogeology topics. This includes but is not limited to: applied geophysics, engineering geomorphology, environmental geology, hydrogeology, groundwater quality, ground source heat, contaminated land, waste management, land use planning, geotechnics, rock mechanics, geomaterials and geological hazards.
The journal publishes the prestigious Glossop and Ineson lectures, research papers, case studies, review articles, technical notes, photographic features, thematic sets, discussion papers, editorial opinion and book reviews.