{"title":"Underwater image color correction and adaptive contrast algorithm improvement based on fusion algorithm","authors":"Hengjun Zhu, Tianluo Wang, Lihao Ma","doi":"10.1117/12.3000979","DOIUrl":null,"url":null,"abstract":"Due to the characteristics of water and the particles in water, the underwater images will have problems of color deviation, low contrast and uneven brightness. Therefore, a statistical approach based on variance is proposed in this paper to correct color-biased images and then equalize the image brightness using the Gamma algorithm. Secondly, a local adaptive contrast enhancement algorithm improved by contrast code images and a restricted contrast adaptive histogram equalization algorithm are used to improve the contrast of underwater images. Finally, two different contrast enhanced images after color correction are fused by a multi-scale fusion algorithm to obtain high-quality underwater images. The results of the comparison experiments with some existing underwater image enhancement algorithms show that our algorithm can effectively improve the quality of underwater images.","PeriodicalId":210802,"journal":{"name":"International Conference on Image Processing and Intelligent Control","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Image Processing and Intelligent Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.3000979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Due to the characteristics of water and the particles in water, the underwater images will have problems of color deviation, low contrast and uneven brightness. Therefore, a statistical approach based on variance is proposed in this paper to correct color-biased images and then equalize the image brightness using the Gamma algorithm. Secondly, a local adaptive contrast enhancement algorithm improved by contrast code images and a restricted contrast adaptive histogram equalization algorithm are used to improve the contrast of underwater images. Finally, two different contrast enhanced images after color correction are fused by a multi-scale fusion algorithm to obtain high-quality underwater images. The results of the comparison experiments with some existing underwater image enhancement algorithms show that our algorithm can effectively improve the quality of underwater images.