{"title":"Underwater Image Enhancement Algorithm Adapted to Different Turbidities Ranges","authors":"Z. Deng, Daxiong Ji, Lizhong Gu, M. Sun, Xin Yao","doi":"10.1109/USYS.2018.8778882","DOIUrl":null,"url":null,"abstract":"This paper proposed an image enhancement method that can adapt to changes in turbidity within a certain range. Establishing illumination intensity attenuation model based on light source carried by robot, we combine the absorption and scattering attenuation factors of the underwater medium with the turbidity of the water to obtain the defuzzified image. This method not only takes into account various complex attenuation media underwater, but also considers the changes in water quality in dynamic scenes. The proposed algorithm can be more adaptive to the motion of underwater robots. It can be seen from the comparative test analysis that the approach has strong robustness in a certain turbidity range.","PeriodicalId":299885,"journal":{"name":"2018 IEEE 8th International Conference on Underwater System Technology: Theory and Applications (USYS)","volume":"3 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 8th International Conference on Underwater System Technology: Theory and Applications (USYS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/USYS.2018.8778882","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
This paper proposed an image enhancement method that can adapt to changes in turbidity within a certain range. Establishing illumination intensity attenuation model based on light source carried by robot, we combine the absorption and scattering attenuation factors of the underwater medium with the turbidity of the water to obtain the defuzzified image. This method not only takes into account various complex attenuation media underwater, but also considers the changes in water quality in dynamic scenes. The proposed algorithm can be more adaptive to the motion of underwater robots. It can be seen from the comparative test analysis that the approach has strong robustness in a certain turbidity range.
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