{"title":"用于水下图像修复的最大信息传递和最小损失去毛刺技术","authors":"Fei Li;Xiaomao Li;Yan Peng;Bin Li;Yang Zhai","doi":"10.1109/JOE.2023.3334478","DOIUrl":null,"url":null,"abstract":"Underwater images typically exhibit color distortion and poor visibility due to light absorption and scattering. Currently, existing methods always overcompensate for degraded color and contrast due to a lack of adaptation, which results in an unnatural appearance and contrast loss. This article combines the merits of conventional color transfer technology and dehazing to improve underwater image quality while addressing the aforementioned problems. Specifically, a maximum information transfer method that does not require a reference image to adaptively correct the color of an input image is first proposed. Built on maximizing contrast while minimizing contrast loss, an adaptive full dynamic range mapping (AFDRM) strategy is then proposed to guide dehazing to restore the visibility. Our method can produce vivid results without introducing over enhancement and is applicable to a variety of underwater environments. Furthermore, with our sufficient and reasonable proof, our method is extended and applied to low-light image enhancement (LLIE) by fine-tuning parameters in this article. Extensive experiments demonstrate that our method achieves superior color correction and contrast enhancement, as well as remarkable performance in underwater applications and low-light scenes, even for foggy images taken at nighttime and daytime.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 2","pages":"622-636"},"PeriodicalIF":3.8000,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Maximum Information Transfer and Minimum Loss Dehazing for Underwater Image Restoration\",\"authors\":\"Fei Li;Xiaomao Li;Yan Peng;Bin Li;Yang Zhai\",\"doi\":\"10.1109/JOE.2023.3334478\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Underwater images typically exhibit color distortion and poor visibility due to light absorption and scattering. Currently, existing methods always overcompensate for degraded color and contrast due to a lack of adaptation, which results in an unnatural appearance and contrast loss. This article combines the merits of conventional color transfer technology and dehazing to improve underwater image quality while addressing the aforementioned problems. Specifically, a maximum information transfer method that does not require a reference image to adaptively correct the color of an input image is first proposed. Built on maximizing contrast while minimizing contrast loss, an adaptive full dynamic range mapping (AFDRM) strategy is then proposed to guide dehazing to restore the visibility. Our method can produce vivid results without introducing over enhancement and is applicable to a variety of underwater environments. Furthermore, with our sufficient and reasonable proof, our method is extended and applied to low-light image enhancement (LLIE) by fine-tuning parameters in this article. Extensive experiments demonstrate that our method achieves superior color correction and contrast enhancement, as well as remarkable performance in underwater applications and low-light scenes, even for foggy images taken at nighttime and daytime.\",\"PeriodicalId\":13191,\"journal\":{\"name\":\"IEEE Journal of Oceanic Engineering\",\"volume\":\"49 2\",\"pages\":\"622-636\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Oceanic Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10388393/\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Oceanic Engineering","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10388393/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Maximum Information Transfer and Minimum Loss Dehazing for Underwater Image Restoration
Underwater images typically exhibit color distortion and poor visibility due to light absorption and scattering. Currently, existing methods always overcompensate for degraded color and contrast due to a lack of adaptation, which results in an unnatural appearance and contrast loss. This article combines the merits of conventional color transfer technology and dehazing to improve underwater image quality while addressing the aforementioned problems. Specifically, a maximum information transfer method that does not require a reference image to adaptively correct the color of an input image is first proposed. Built on maximizing contrast while minimizing contrast loss, an adaptive full dynamic range mapping (AFDRM) strategy is then proposed to guide dehazing to restore the visibility. Our method can produce vivid results without introducing over enhancement and is applicable to a variety of underwater environments. Furthermore, with our sufficient and reasonable proof, our method is extended and applied to low-light image enhancement (LLIE) by fine-tuning parameters in this article. Extensive experiments demonstrate that our method achieves superior color correction and contrast enhancement, as well as remarkable performance in underwater applications and low-light scenes, even for foggy images taken at nighttime and daytime.
期刊介绍:
The IEEE Journal of Oceanic Engineering (ISSN 0364-9059) is the online-only quarterly publication of the IEEE Oceanic Engineering Society (IEEE OES). The scope of the Journal is the field of interest of the IEEE OES, which encompasses all aspects of science, engineering, and technology that address research, development, and operations pertaining to all bodies of water. This includes the creation of new capabilities and technologies from concept design through prototypes, testing, and operational systems to sense, explore, understand, develop, use, and responsibly manage natural resources.