{"title":"FEUWNet:一种快速有效的水下图像增强基线","authors":"Xinkui Mei, Xiufen Ye, Junting Wang, Shengya Zhao","doi":"10.1109/ICMA57826.2023.10215650","DOIUrl":null,"url":null,"abstract":"Underwater optical images are one of the important media for humans to explore the oceans, but it is difficult to directly obtain high-quality underwater images because of the unique physical and chemical properties of underwater, most underwater images exhibit disadvantages such as color decay, low contrast, and blurred details. In order to solve the above problems, this paper designed a fast and effective baseline for underwater image enhancement called FEUWNet. FEUWNet uses a plug-and-play module consists with downsampling encoding block and up-sampling decoding block to balance enhancement performance and computational speed. After experimental comparison, FEUWNet has achieved good results in underwater image enhancement.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"FEUWNet: A Fast and Effective Baseline for Underwater Image Enhancement\",\"authors\":\"Xinkui Mei, Xiufen Ye, Junting Wang, Shengya Zhao\",\"doi\":\"10.1109/ICMA57826.2023.10215650\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Underwater optical images are one of the important media for humans to explore the oceans, but it is difficult to directly obtain high-quality underwater images because of the unique physical and chemical properties of underwater, most underwater images exhibit disadvantages such as color decay, low contrast, and blurred details. In order to solve the above problems, this paper designed a fast and effective baseline for underwater image enhancement called FEUWNet. FEUWNet uses a plug-and-play module consists with downsampling encoding block and up-sampling decoding block to balance enhancement performance and computational speed. After experimental comparison, FEUWNet has achieved good results in underwater image enhancement.\",\"PeriodicalId\":151364,\"journal\":{\"name\":\"2023 IEEE International Conference on Mechatronics and Automation (ICMA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Mechatronics and Automation (ICMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMA57826.2023.10215650\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA57826.2023.10215650","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
FEUWNet: A Fast and Effective Baseline for Underwater Image Enhancement
Underwater optical images are one of the important media for humans to explore the oceans, but it is difficult to directly obtain high-quality underwater images because of the unique physical and chemical properties of underwater, most underwater images exhibit disadvantages such as color decay, low contrast, and blurred details. In order to solve the above problems, this paper designed a fast and effective baseline for underwater image enhancement called FEUWNet. FEUWNet uses a plug-and-play module consists with downsampling encoding block and up-sampling decoding block to balance enhancement performance and computational speed. After experimental comparison, FEUWNet has achieved good results in underwater image enhancement.