The performance of speckle ﬁlters on Copernicus Sentinel-1 SAR images containing natural oil slicks

IF 1.3 4区工程技术 Q3 ENGINEERING, GEOLOGICAL

Quarterly Journal of Engineering Geology and Hydrogeology Pub Date : 2023-03-31 DOI:10.1144/qjegh2022-046

C. Vrinceanu, S. Grebby, S. Marsh

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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

查看原文本刊更多论文

斑点滤波器在含天然浮油的哥白尼Sentinel-1 SAR图像上的性能

合成孔径雷达(SAR)传统上用于石油浮油的识别、测绘和分析，无论其来源如何。在SAR图像上，浮油呈现为深色斑块，与周围明亮的海面形成鲜明对比。这种区别允许使用计算机视觉方法设计自动检测算法来客观识别浮油。然而，由于SAR图像上存在散斑效应，统计分析对SAR图像的有效解释可能会降低，这是一种与SAR相干性相关的颗粒状伪影，在视觉上降低了图像质量。本文对常用的SAR图像去斑方法进行了定量和定性评价，分析了它们在含天然浮油图像上的性能。评估是在不同时间和环境条件下获得的哥白尼哨兵1号图像上进行的。评估涵盖了在空间、变换和小波域采用贝叶斯和非线性统计的滤波器的不同领域，重点关注它们在边缘和纹理保留方面的表现和能力。总之，结果表明，在空间域中使用局部统计的滤波器产生一致的预期效果。新的SAR-BM3D算法虽然具有较高的计算量，但可以有效地使用。补充材料:本文中使用的散斑过滤器的实现可以在:https://github.com/cavrinceanu/specklefilters获得MIT许可。表3-11的图像统计数据可在以下网址获得:https://doi.org/10.6084/m9.figshare.13010405专题收集:本文是地球和其他行星现场调查遥感收集的一部分:https://www.lyellcollection.org/cc/remote-sensing-for-site-investigations-on-earth-and-other-planets

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来源期刊

Quarterly Journal of Engineering Geology and Hydrogeology 地学-地球科学综合

CiteScore

3.40

自引率

14.30%

发文量

审稿时长

6 months

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.