A Review of Methods for Ship Detection with Electro-Optical Images in Marine Environments
The ocean connects all continents and is an important space for human activities. Ship detection with electro-optical images has shown great potential due to the abundant imaging spectrum and, hence, strongly supports human activities in the ocean. A suitable imaging spectrum can obtain effective im...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
|
| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/9/12/1408 |
| _version_ | 1797503235570794496 |
|---|---|
| author | Liqian Wang Shuzhen Fan Yunxia Liu Yongfu Li Cheng Fei Junliang Liu Bohan Liu Yakui Dong Zhaojun Liu Xian Zhao |
| author_facet | Liqian Wang Shuzhen Fan Yunxia Liu Yongfu Li Cheng Fei Junliang Liu Bohan Liu Yakui Dong Zhaojun Liu Xian Zhao |
| author_sort | Liqian Wang |
| collection | DOAJ |
| description | The ocean connects all continents and is an important space for human activities. Ship detection with electro-optical images has shown great potential due to the abundant imaging spectrum and, hence, strongly supports human activities in the ocean. A suitable imaging spectrum can obtain effective images in complex marine environments, which is the premise of ship detection. This paper provides an overview of ship detection methods with electro-optical images in marine environments. Ship detection methods with sea–sky backgrounds include traditional and deep learning methods. Traditional ship detection methods comprise the following steps: preprocessing, sea–sky line (SSL) detection, region of interest (ROI) extraction, and identification. The use of deep learning is promising in ship detection; however, it requires a large amount of labeled data to build a robust model, and its targeted optimization for ship detection in marine environments is not sufficient. |
| first_indexed | 2024-03-10T03:47:39Z |
| format | Article |
| id | doaj.art-337a69eb12614812bc27ecf741302ab5 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-10T03:47:39Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-337a69eb12614812bc27ecf741302ab52023-11-23T09:03:21ZengMDPI AGJournal of Marine Science and Engineering2077-13122021-12-01912140810.3390/jmse9121408A Review of Methods for Ship Detection with Electro-Optical Images in Marine EnvironmentsLiqian Wang0Shuzhen Fan1Yunxia Liu2Yongfu Li3Cheng Fei4Junliang Liu5Bohan Liu6Yakui Dong7Zhaojun Liu8Xian Zhao9Key Laboratory of Laser & Infrared System, Shandong University, Ministry of Education, 72 Binhai Road, Qingdao 266237, ChinaKey Laboratory of Laser & Infrared System, Shandong University, Ministry of Education, 72 Binhai Road, Qingdao 266237, ChinaKey Laboratory of Laser & Infrared System, Shandong University, Ministry of Education, 72 Binhai Road, Qingdao 266237, ChinaKey Laboratory of Laser & Infrared System, Shandong University, Ministry of Education, 72 Binhai Road, Qingdao 266237, ChinaKey Laboratory of Laser & Infrared System, Shandong University, Ministry of Education, 72 Binhai Road, Qingdao 266237, ChinaKey Laboratory of Laser & Infrared System, Shandong University, Ministry of Education, 72 Binhai Road, Qingdao 266237, ChinaKey Laboratory of Laser & Infrared System, Shandong University, Ministry of Education, 72 Binhai Road, Qingdao 266237, ChinaKey Laboratory of Laser & Infrared System, Shandong University, Ministry of Education, 72 Binhai Road, Qingdao 266237, ChinaKey Laboratory of Laser & Infrared System, Shandong University, Ministry of Education, 72 Binhai Road, Qingdao 266237, ChinaKey Laboratory of Laser & Infrared System, Shandong University, Ministry of Education, 72 Binhai Road, Qingdao 266237, ChinaThe ocean connects all continents and is an important space for human activities. Ship detection with electro-optical images has shown great potential due to the abundant imaging spectrum and, hence, strongly supports human activities in the ocean. A suitable imaging spectrum can obtain effective images in complex marine environments, which is the premise of ship detection. This paper provides an overview of ship detection methods with electro-optical images in marine environments. Ship detection methods with sea–sky backgrounds include traditional and deep learning methods. Traditional ship detection methods comprise the following steps: preprocessing, sea–sky line (SSL) detection, region of interest (ROI) extraction, and identification. The use of deep learning is promising in ship detection; however, it requires a large amount of labeled data to build a robust model, and its targeted optimization for ship detection in marine environments is not sufficient.https://www.mdpi.com/2077-1312/9/12/1408ship detectionvessel detectionelectro-optical images processingship monitoring |
| spellingShingle | Liqian Wang Shuzhen Fan Yunxia Liu Yongfu Li Cheng Fei Junliang Liu Bohan Liu Yakui Dong Zhaojun Liu Xian Zhao A Review of Methods for Ship Detection with Electro-Optical Images in Marine Environments Journal of Marine Science and Engineering ship detection vessel detection electro-optical images processing ship monitoring |
| title | A Review of Methods for Ship Detection with Electro-Optical Images in Marine Environments |
| title_full | A Review of Methods for Ship Detection with Electro-Optical Images in Marine Environments |
| title_fullStr | A Review of Methods for Ship Detection with Electro-Optical Images in Marine Environments |
| title_full_unstemmed | A Review of Methods for Ship Detection with Electro-Optical Images in Marine Environments |
| title_short | A Review of Methods for Ship Detection with Electro-Optical Images in Marine Environments |
| title_sort | review of methods for ship detection with electro optical images in marine environments |
| topic | ship detection vessel detection electro-optical images processing ship monitoring |
| url | https://www.mdpi.com/2077-1312/9/12/1408 |
| work_keys_str_mv | AT liqianwang areviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT shuzhenfan areviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT yunxialiu areviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT yongfuli areviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT chengfei areviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT junliangliu areviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT bohanliu areviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT yakuidong areviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT zhaojunliu areviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT xianzhao areviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT liqianwang reviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT shuzhenfan reviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT yunxialiu reviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT yongfuli reviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT chengfei reviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT junliangliu reviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT bohanliu reviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT yakuidong reviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT zhaojunliu reviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments AT xianzhao reviewofmethodsforshipdetectionwithelectroopticalimagesinmarineenvironments |