Integrating Incidence Angle Dependencies Into the Clustering-Based Segmentation of SAR Images
Synthetic aperture radar systems perform signal acquisition under varying incidence angles and register an implicit intensity decay from near to far range. Owing to the geometrical interaction between microwaves and the imaged targets, the rates at which intensities decay depend on the nature of the...
Published in: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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Online Access: | https://hdl.handle.net/10037/21036 https://doi.org/10.1109/JSTARS.2020.2993067 |
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ftunivtroemsoe:oai:munin.uit.no:10037/21036 2023-05-15T14:27:27+02:00 Integrating Incidence Angle Dependencies Into the Clustering-Based Segmentation of SAR Images Cristea, Anca Van Houtte, Jeroen Doulgeris, Anthony Paul 2020-05-28 https://hdl.handle.net/10037/21036 https://doi.org/10.1109/JSTARS.2020.2993067 eng eng Institute of Electrical and Electronics Engineers (IEEE) IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Norges forskningsråd: 237906 info:eu-repo/grantAgreement/RCN/SFI/237906/Norway/Centre for Integrated Remote Sensing and Forecasting for Arctic Operations/CIRFA/ Cristea A, Van Houtte, Doulgeris ap. Integrating Incidence Angle Dependencies Into the Clustering-Based Segmentation of SAR Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020;13(1) FRIDAID 1816179 doi:10.1109/JSTARS.2020.2993067 1939-1404 2151-1535 https://hdl.handle.net/10037/21036 openAccess Copyright 2020 The Author(s) VDP::Technology: 500 VDP::Teknologi: 500 Journal article Tidsskriftartikkel Peer reviewed publishedVersion 2020 ftunivtroemsoe https://doi.org/10.1109/JSTARS.2020.2993067 2021-06-25T17:57:58Z Synthetic aperture radar systems perform signal acquisition under varying incidence angles and register an implicit intensity decay from near to far range. Owing to the geometrical interaction between microwaves and the imaged targets, the rates at which intensities decay depend on the nature of the targets, thus rendering single-rate image correction approaches only partially successful. The decay, also known as the incidence angle effect, impacts the segmentation of wide-swath images performed on absolute intensity values. We propose to integrate the target-specific intensity decay rates into a nonstationary statistical model, for use in a fully automatic and unsupervised segmentation algorithm. We demonstrate this concept by assuming Gaussian distributed log-intensities and linear decay rates, a fitting approximation for the smooth systematic decay observed for extended flat targets. The segmentation is performed on Sentinel-1, Radarsat-2, and UAVSAR wide-swath scenes containing open water, sea ice, and oil slicks. As a result, we obtain segments connected throughout the entire incidence angle range, thus overcoming the limitations of modeling that does not account for different per-target decays. The model simplicity also allows for short execution times and presents the segmentation approach as a potential operational algorithm. In addition, we estimate the log-linear decay rates and examine their potential for a physical interpretation of the segments. Article in Journal/Newspaper Arctic Sea ice University of Tromsø: Munin Open Research Archive IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13 2925 2939 |
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Open Polar |
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University of Tromsø: Munin Open Research Archive |
op_collection_id |
ftunivtroemsoe |
language |
English |
topic |
VDP::Technology: 500 VDP::Teknologi: 500 |
spellingShingle |
VDP::Technology: 500 VDP::Teknologi: 500 Cristea, Anca Van Houtte, Jeroen Doulgeris, Anthony Paul Integrating Incidence Angle Dependencies Into the Clustering-Based Segmentation of SAR Images |
topic_facet |
VDP::Technology: 500 VDP::Teknologi: 500 |
description |
Synthetic aperture radar systems perform signal acquisition under varying incidence angles and register an implicit intensity decay from near to far range. Owing to the geometrical interaction between microwaves and the imaged targets, the rates at which intensities decay depend on the nature of the targets, thus rendering single-rate image correction approaches only partially successful. The decay, also known as the incidence angle effect, impacts the segmentation of wide-swath images performed on absolute intensity values. We propose to integrate the target-specific intensity decay rates into a nonstationary statistical model, for use in a fully automatic and unsupervised segmentation algorithm. We demonstrate this concept by assuming Gaussian distributed log-intensities and linear decay rates, a fitting approximation for the smooth systematic decay observed for extended flat targets. The segmentation is performed on Sentinel-1, Radarsat-2, and UAVSAR wide-swath scenes containing open water, sea ice, and oil slicks. As a result, we obtain segments connected throughout the entire incidence angle range, thus overcoming the limitations of modeling that does not account for different per-target decays. The model simplicity also allows for short execution times and presents the segmentation approach as a potential operational algorithm. In addition, we estimate the log-linear decay rates and examine their potential for a physical interpretation of the segments. |
format |
Article in Journal/Newspaper |
author |
Cristea, Anca Van Houtte, Jeroen Doulgeris, Anthony Paul |
author_facet |
Cristea, Anca Van Houtte, Jeroen Doulgeris, Anthony Paul |
author_sort |
Cristea, Anca |
title |
Integrating Incidence Angle Dependencies Into the Clustering-Based Segmentation of SAR Images |
title_short |
Integrating Incidence Angle Dependencies Into the Clustering-Based Segmentation of SAR Images |
title_full |
Integrating Incidence Angle Dependencies Into the Clustering-Based Segmentation of SAR Images |
title_fullStr |
Integrating Incidence Angle Dependencies Into the Clustering-Based Segmentation of SAR Images |
title_full_unstemmed |
Integrating Incidence Angle Dependencies Into the Clustering-Based Segmentation of SAR Images |
title_sort |
integrating incidence angle dependencies into the clustering-based segmentation of sar images |
publisher |
Institute of Electrical and Electronics Engineers (IEEE) |
publishDate |
2020 |
url |
https://hdl.handle.net/10037/21036 https://doi.org/10.1109/JSTARS.2020.2993067 |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_relation |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Norges forskningsråd: 237906 info:eu-repo/grantAgreement/RCN/SFI/237906/Norway/Centre for Integrated Remote Sensing and Forecasting for Arctic Operations/CIRFA/ Cristea A, Van Houtte, Doulgeris ap. Integrating Incidence Angle Dependencies Into the Clustering-Based Segmentation of SAR Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020;13(1) FRIDAID 1816179 doi:10.1109/JSTARS.2020.2993067 1939-1404 2151-1535 https://hdl.handle.net/10037/21036 |
op_rights |
openAccess Copyright 2020 The Author(s) |
op_doi |
https://doi.org/10.1109/JSTARS.2020.2993067 |
container_title |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
container_volume |
13 |
container_start_page |
2925 |
op_container_end_page |
2939 |
_version_ |
1766301198520942592 |