{"title":"Underwater Image Enhancement Using Illuminant Intensity Compensation With Foreground Edge Map Rectification","authors":"Herng-Hua Chang;Pin-Yi Kuan","doi":"10.1109/JOE.2024.3523372","DOIUrl":null,"url":null,"abstract":"Underwater image enhancement has been paid more attention in recent years as it is a fundamental task in many relevant image processing applications. This article investigates a new underwater image enhancement algorithm based on a simplified image formation model established by the integration of the Jaffe–McGlamery and Lambertian systems. The retinex theory is introduced into the prototype to explicitly disclose the illuminant intensity, which is computed using an efficient gray index scheme for light source attenuation compensation. Subsequently, an improved scene depth estimation method is exploited to separate the foreground from the background, upon which a foreground edge map is computed for better background light determination. Finally, an ensemble color gain is appraised to correct the color deviation. A wide variety of underwater images with various scenarios in six different data sets were employed to evaluate the proposed image enhancement system. Experimental results demonstrated the advantages of our underwater image enhancement algorithm over many state-of-the-art methods both qualitatively and quantitatively. It is believed that the developed image enhancement framework has potential in many underwater image processing applications.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 2","pages":"835-850"},"PeriodicalIF":3.8000,"publicationDate":"2025-02-11","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/10880663/","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
Abstract
Underwater image enhancement has been paid more attention in recent years as it is a fundamental task in many relevant image processing applications. This article investigates a new underwater image enhancement algorithm based on a simplified image formation model established by the integration of the Jaffe–McGlamery and Lambertian systems. The retinex theory is introduced into the prototype to explicitly disclose the illuminant intensity, which is computed using an efficient gray index scheme for light source attenuation compensation. Subsequently, an improved scene depth estimation method is exploited to separate the foreground from the background, upon which a foreground edge map is computed for better background light determination. Finally, an ensemble color gain is appraised to correct the color deviation. A wide variety of underwater images with various scenarios in six different data sets were employed to evaluate the proposed image enhancement system. Experimental results demonstrated the advantages of our underwater image enhancement algorithm over many state-of-the-art methods both qualitatively and quantitatively. It is believed that the developed image enhancement framework has potential in many underwater image processing applications.
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.