A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary Satellite
Geostationary optical remote sensing satellites, such as the GF-4, have a high temporal resolution and wide coverage, which enables the continuous tracking and observation of ship targets over a large range. However, the ship targets in the images are usually small and dim and the images are easily...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/22/7547 |
| _version_ | 1797508523214503936 |
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| author | Wei Yu Hongjian You Peng Lv Yuxin Hu Bing Han |
| author_facet | Wei Yu Hongjian You Peng Lv Yuxin Hu Bing Han |
| author_sort | Wei Yu |
| collection | DOAJ |
| description | Geostationary optical remote sensing satellites, such as the GF-4, have a high temporal resolution and wide coverage, which enables the continuous tracking and observation of ship targets over a large range. However, the ship targets in the images are usually small and dim and the images are easily affected by clouds, islands and other factors, which make it difficult to detect the ship targets. This paper proposes a new method for detecting ships moving on the sea surface using GF-4 satellite images. First, the adaptive nonlinear gray stretch (ANGS) method was used to enhance the image and highlight small and dim ship targets. Second, a multi-scale dual-neighbor difference contrast measure (MDDCM) method was designed to enable detection of the position of the candidate ship target. The shape characteristics of each candidate area were analyzed to remove false ship targets. Finally, the joint probability data association (JPDA) method was used for multi-frame data association and tracking. Our results suggest that the proposed method can effectively detect and track moving ship targets in GF-4 satellite optical remote sensing images, with better detection performance than other classical methods. |
| first_indexed | 2024-03-10T05:05:07Z |
| format | Article |
| id | doaj.art-8b1f48341bb24c7a88f1112af5a91991 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T05:05:07Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8b1f48341bb24c7a88f1112af5a919912023-11-23T01:25:19ZengMDPI AGSensors1424-82202021-11-012122754710.3390/s21227547A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary SatelliteWei Yu0Hongjian You1Peng Lv2Yuxin Hu3Bing Han4Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaGeostationary optical remote sensing satellites, such as the GF-4, have a high temporal resolution and wide coverage, which enables the continuous tracking and observation of ship targets over a large range. However, the ship targets in the images are usually small and dim and the images are easily affected by clouds, islands and other factors, which make it difficult to detect the ship targets. This paper proposes a new method for detecting ships moving on the sea surface using GF-4 satellite images. First, the adaptive nonlinear gray stretch (ANGS) method was used to enhance the image and highlight small and dim ship targets. Second, a multi-scale dual-neighbor difference contrast measure (MDDCM) method was designed to enable detection of the position of the candidate ship target. The shape characteristics of each candidate area were analyzed to remove false ship targets. Finally, the joint probability data association (JPDA) method was used for multi-frame data association and tracking. Our results suggest that the proposed method can effectively detect and track moving ship targets in GF-4 satellite optical remote sensing images, with better detection performance than other classical methods.https://www.mdpi.com/1424-8220/21/22/7547geostationary orbit satellitesGF-4 satellitesship detectionship trackingvisual saliencydata association |
| spellingShingle | Wei Yu Hongjian You Peng Lv Yuxin Hu Bing Han A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary Satellite Sensors geostationary orbit satellites GF-4 satellites ship detection ship tracking visual saliency data association |
| title | A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary Satellite |
| title_full | A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary Satellite |
| title_fullStr | A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary Satellite |
| title_full_unstemmed | A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary Satellite |
| title_short | A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary Satellite |
| title_sort | moving ship detection and tracking method based on optical remote sensing images from the geostationary satellite |
| topic | geostationary orbit satellites GF-4 satellites ship detection ship tracking visual saliency data association |
| url | https://www.mdpi.com/1424-8220/21/22/7547 |
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