Ship Detection in SAR Image Based on the Alpha-stable Distribution
This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alphastable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2008-08-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/8/8/4948/ |
| _version_ | 1828150086191808512 |
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| author | Xiaofeng Li Mingsheng Liao Changcheng Wang |
| author_facet | Xiaofeng Li Mingsheng Liao Changcheng Wang |
| author_sort | Xiaofeng Li |
| collection | DOAJ |
| description | This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alphastable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution. |
| first_indexed | 2024-04-11T21:39:22Z |
| format | Article |
| id | doaj.art-5c681c2925e742fd8a68d747bafc6ddd |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T21:39:22Z |
| publishDate | 2008-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5c681c2925e742fd8a68d747bafc6ddd2022-12-22T04:01:39ZengMDPI AGSensors1424-82202008-08-018849484960Ship Detection in SAR Image Based on the Alpha-stable DistributionXiaofeng LiMingsheng LiaoChangcheng WangThis paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alphastable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution.http://www.mdpi.com/1424-8220/8/8/4948/Alpha-stable distributionship detectionSynthetic Aperture RadarConstant False Alarm Rate (CFAR). |
| spellingShingle | Xiaofeng Li Mingsheng Liao Changcheng Wang Ship Detection in SAR Image Based on the Alpha-stable Distribution Sensors Alpha-stable distribution ship detection Synthetic Aperture Radar Constant False Alarm Rate (CFAR). |
| title | Ship Detection in SAR Image Based on the Alpha-stable Distribution |
| title_full | Ship Detection in SAR Image Based on the Alpha-stable Distribution |
| title_fullStr | Ship Detection in SAR Image Based on the Alpha-stable Distribution |
| title_full_unstemmed | Ship Detection in SAR Image Based on the Alpha-stable Distribution |
| title_short | Ship Detection in SAR Image Based on the Alpha-stable Distribution |
| title_sort | ship detection in sar image based on the alpha stable distribution |
| topic | Alpha-stable distribution ship detection Synthetic Aperture Radar Constant False Alarm Rate (CFAR). |
| url | http://www.mdpi.com/1424-8220/8/8/4948/ |
| work_keys_str_mv | AT xiaofengli shipdetectioninsarimagebasedonthealphastabledistribution AT mingshengliao shipdetectioninsarimagebasedonthealphastabledistribution AT changchengwang shipdetectioninsarimagebasedonthealphastabledistribution |