Dan Xiang, Huihua Wang, Zebin Zhou, Hao Zhao, Pan Gao, Jinwen Zhang, Chun Shan
{"title":"基于加权导向滤波图像融合的水下图像增强技术","authors":"Dan Xiang, Huihua Wang, Zebin Zhou, Hao Zhao, Pan Gao, Jinwen Zhang, Chun Shan","doi":"10.1007/s00530-024-01432-7","DOIUrl":null,"url":null,"abstract":"<p>An underwater image enhancement technique based on weighted guided filter image fusion is proposed to address challenges, including optical absorption and scattering, color distortion, and uneven illumination. The method consists of three stages: color correction, local contrast enhancement, and fusion algorithm methods. In terms of color correction, basic correction is achieved through channel compensation and remapping, with saturation adjusted based on histogram distribution to enhance visual richness. For local contrast enhancement, the approach involves box filtering and a variational model to improve image saturation. Finally, the method utilizes weighted guided filter image fusion to achieve high visual quality underwater images. Additionally, our method outperforms eight state-of-the-art algorithms in no-reference metrics, demonstrating its effectiveness and innovation. We also conducted application tests and time comparisons to further validate the practicality of our approach.</p>","PeriodicalId":51138,"journal":{"name":"Multimedia Systems","volume":"43 1","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Underwater image enhancement based on weighted guided filter image fusion\",\"authors\":\"Dan Xiang, Huihua Wang, Zebin Zhou, Hao Zhao, Pan Gao, Jinwen Zhang, Chun Shan\",\"doi\":\"10.1007/s00530-024-01432-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>An underwater image enhancement technique based on weighted guided filter image fusion is proposed to address challenges, including optical absorption and scattering, color distortion, and uneven illumination. The method consists of three stages: color correction, local contrast enhancement, and fusion algorithm methods. In terms of color correction, basic correction is achieved through channel compensation and remapping, with saturation adjusted based on histogram distribution to enhance visual richness. For local contrast enhancement, the approach involves box filtering and a variational model to improve image saturation. Finally, the method utilizes weighted guided filter image fusion to achieve high visual quality underwater images. Additionally, our method outperforms eight state-of-the-art algorithms in no-reference metrics, demonstrating its effectiveness and innovation. We also conducted application tests and time comparisons to further validate the practicality of our approach.</p>\",\"PeriodicalId\":51138,\"journal\":{\"name\":\"Multimedia Systems\",\"volume\":\"43 1\",\"pages\":\"\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Multimedia Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s00530-024-01432-7\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multimedia Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s00530-024-01432-7","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Underwater image enhancement based on weighted guided filter image fusion
An underwater image enhancement technique based on weighted guided filter image fusion is proposed to address challenges, including optical absorption and scattering, color distortion, and uneven illumination. The method consists of three stages: color correction, local contrast enhancement, and fusion algorithm methods. In terms of color correction, basic correction is achieved through channel compensation and remapping, with saturation adjusted based on histogram distribution to enhance visual richness. For local contrast enhancement, the approach involves box filtering and a variational model to improve image saturation. Finally, the method utilizes weighted guided filter image fusion to achieve high visual quality underwater images. Additionally, our method outperforms eight state-of-the-art algorithms in no-reference metrics, demonstrating its effectiveness and innovation. We also conducted application tests and time comparisons to further validate the practicality of our approach.
期刊介绍:
This journal details innovative research ideas, emerging technologies, state-of-the-art methods and tools in all aspects of multimedia computing, communication, storage, and applications. It features theoretical, experimental, and survey articles.