{"title":"Mutually Guided Image Dehazing","authors":"Usman Ali, W. T. Toor","doi":"10.1109/ICETECC56662.2022.10069696","DOIUrl":null,"url":null,"abstract":"This paper presents an efficient regularization scheme for the single image dehazing. The transmission map has been reguarlized to retrieve a dehazed image. Usually, conventional methods try to improve the initial transmission through guided filtering without considering the potential advantage of improving the guidance as well. We have proposed an efficient regularization scheme that jointly optimizes the transmission map and the guidance. Nonconvex energy function is solved by iterative reweighed least squares. As a result, an improved transmission map is obtained that has edges concurrent with the iteratively updated guidance. The regularized transmission map results in better-quality dehazed image which has improved color fidelity and fine details as demonstrated by the experimental results.","PeriodicalId":364463,"journal":{"name":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETECC56662.2022.10069696","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
This paper presents an efficient regularization scheme for the single image dehazing. The transmission map has been reguarlized to retrieve a dehazed image. Usually, conventional methods try to improve the initial transmission through guided filtering without considering the potential advantage of improving the guidance as well. We have proposed an efficient regularization scheme that jointly optimizes the transmission map and the guidance. Nonconvex energy function is solved by iterative reweighed least squares. As a result, an improved transmission map is obtained that has edges concurrent with the iteratively updated guidance. The regularized transmission map results in better-quality dehazed image which has improved color fidelity and fine details as demonstrated by the experimental results.