Study on the Classification Perception and Visibility Enhancement of Ship Navigation Environments in Foggy Conditions
Based on ship navigational requirements and safety in foggy conditions and with a particular emphasis on avoiding ship collisions and improving navigational abilities, we constructed a fog navigation dataset along with a new method for enhancing foggy images and perceived visibility using a discrimi...
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-06-01
|
| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/11/7/1298 |
| _version_ | 1797588792030265344 |
|---|---|
| author | Chiming Wang Boyan Fan Yanan Li Jingjing Xiao Lanxi Min Jing Zhang Jiuhu Chen Zhong Lin Sunxin Su Rongjiong Wu Shunzhi Zhu |
| author_facet | Chiming Wang Boyan Fan Yanan Li Jingjing Xiao Lanxi Min Jing Zhang Jiuhu Chen Zhong Lin Sunxin Su Rongjiong Wu Shunzhi Zhu |
| author_sort | Chiming Wang |
| collection | DOAJ |
| description | Based on ship navigational requirements and safety in foggy conditions and with a particular emphasis on avoiding ship collisions and improving navigational abilities, we constructed a fog navigation dataset along with a new method for enhancing foggy images and perceived visibility using a discriminant deep learning architecture and the EfficientNet neural network by replacing the SE module and incorporating a convolution block attention module and focal loss function. The accuracy of our model exceeded 95%, which meets the needs of an intelligent ship navigation environment in foggy conditions. As part of our research, we also determined the best enhancement algorithm for each type of fog according to its classification. |
| first_indexed | 2024-03-11T00:57:04Z |
| format | Article |
| id | doaj.art-c0aa2741fee84e7d911979fb38b60e53 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-11T00:57:04Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-c0aa2741fee84e7d911979fb38b60e532023-11-18T19:58:11ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-06-01117129810.3390/jmse11071298Study on the Classification Perception and Visibility Enhancement of Ship Navigation Environments in Foggy ConditionsChiming Wang0Boyan Fan1Yanan Li2Jingjing Xiao3Lanxi Min4Jing Zhang5Jiuhu Chen6Zhong Lin7Sunxin Su8Rongjiong Wu9Shunzhi Zhu10School of Computer and Information Engineering, Xiamen Institute of Technology, Xiamen 361024, ChinaSchool of Computer and Information Engineering, Xiamen Institute of Technology, Xiamen 361024, ChinaSchool of Computer and Information Engineering, Xiamen Institute of Technology, Xiamen 361024, ChinaSchool of Computer and Information Engineering, Xiamen Institute of Technology, Xiamen 361024, ChinaSchool of Computer and Information Engineering, Xiamen Institute of Technology, Xiamen 361024, ChinaSchool of Computer and Information Engineering, Xiamen Institute of Technology, Xiamen 361024, ChinaFujian Xinji Shipping Service Co. Ltd., Xiamen 361000, ChinaFujian Xinji Shipping Service Co. Ltd., Xiamen 361000, ChinaFujian Xinji Shipping Service Co. Ltd., Xiamen 361000, ChinaSchool of Computer and Information Engineering, Xiamen Institute of Technology, Xiamen 361024, ChinaSchool of Computer and Information Engineering, Xiamen Institute of Technology, Xiamen 361024, ChinaBased on ship navigational requirements and safety in foggy conditions and with a particular emphasis on avoiding ship collisions and improving navigational abilities, we constructed a fog navigation dataset along with a new method for enhancing foggy images and perceived visibility using a discriminant deep learning architecture and the EfficientNet neural network by replacing the SE module and incorporating a convolution block attention module and focal loss function. The accuracy of our model exceeded 95%, which meets the needs of an intelligent ship navigation environment in foggy conditions. As part of our research, we also determined the best enhancement algorithm for each type of fog according to its classification.https://www.mdpi.com/2077-1312/11/7/1298deep learningvisibility classificationenvironment perceptionimage enhancement |
| spellingShingle | Chiming Wang Boyan Fan Yanan Li Jingjing Xiao Lanxi Min Jing Zhang Jiuhu Chen Zhong Lin Sunxin Su Rongjiong Wu Shunzhi Zhu Study on the Classification Perception and Visibility Enhancement of Ship Navigation Environments in Foggy Conditions Journal of Marine Science and Engineering deep learning visibility classification environment perception image enhancement |
| title | Study on the Classification Perception and Visibility Enhancement of Ship Navigation Environments in Foggy Conditions |
| title_full | Study on the Classification Perception and Visibility Enhancement of Ship Navigation Environments in Foggy Conditions |
| title_fullStr | Study on the Classification Perception and Visibility Enhancement of Ship Navigation Environments in Foggy Conditions |
| title_full_unstemmed | Study on the Classification Perception and Visibility Enhancement of Ship Navigation Environments in Foggy Conditions |
| title_short | Study on the Classification Perception and Visibility Enhancement of Ship Navigation Environments in Foggy Conditions |
| title_sort | study on the classification perception and visibility enhancement of ship navigation environments in foggy conditions |
| topic | deep learning visibility classification environment perception image enhancement |
| url | https://www.mdpi.com/2077-1312/11/7/1298 |
| work_keys_str_mv | AT chimingwang studyontheclassificationperceptionandvisibilityenhancementofshipnavigationenvironmentsinfoggyconditions AT boyanfan studyontheclassificationperceptionandvisibilityenhancementofshipnavigationenvironmentsinfoggyconditions AT yananli studyontheclassificationperceptionandvisibilityenhancementofshipnavigationenvironmentsinfoggyconditions AT jingjingxiao studyontheclassificationperceptionandvisibilityenhancementofshipnavigationenvironmentsinfoggyconditions AT lanximin studyontheclassificationperceptionandvisibilityenhancementofshipnavigationenvironmentsinfoggyconditions AT jingzhang studyontheclassificationperceptionandvisibilityenhancementofshipnavigationenvironmentsinfoggyconditions AT jiuhuchen studyontheclassificationperceptionandvisibilityenhancementofshipnavigationenvironmentsinfoggyconditions AT zhonglin studyontheclassificationperceptionandvisibilityenhancementofshipnavigationenvironmentsinfoggyconditions AT sunxinsu studyontheclassificationperceptionandvisibilityenhancementofshipnavigationenvironmentsinfoggyconditions AT rongjiongwu studyontheclassificationperceptionandvisibilityenhancementofshipnavigationenvironmentsinfoggyconditions AT shunzhizhu studyontheclassificationperceptionandvisibilityenhancementofshipnavigationenvironmentsinfoggyconditions |