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

IF 3.8 2区 工程技术 Q1 ENGINEERING, CIVIL
Fei Li;Xiaomao Li;Yan Peng;Bin Li;Yang Zhai
{"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}
引用次数: 0

摘要

由于光的吸收和散射,水下图像通常会出现色彩失真和可视性差的问题。目前,由于缺乏适应性,现有方法总是过度补偿色彩和对比度的劣化,从而导致不自然的外观和对比度损失。本文结合了传统色彩转移技术和去色差技术的优点,在改善水下图像质量的同时解决了上述问题。具体来说,本文首先提出了一种无需参考图像的最大信息传输方法,用于自适应校正输入图像的颜色。在最大化对比度的同时最小化对比度损失的基础上,提出了一种自适应全动态范围映射(AFDRM)策略来指导去毛刺以恢复可见度。我们的方法可以在不引入过度增强的情况下产生生动的效果,并且适用于各种水下环境。此外,在我们充分、合理的论证下,本文通过微调参数,将我们的方法扩展并应用于低照度图像增强(LLIE)。大量实验证明,我们的方法实现了卓越的色彩校正和对比度增强,并在水下应用和低光场景中表现出色,即使是夜间和白天拍摄的雾气图像也不例外。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
IEEE Journal of Oceanic Engineering
IEEE Journal of Oceanic Engineering 工程技术-工程:大洋
CiteScore
9.60
自引率
12.20%
发文量
86
审稿时长
12 months
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信