{"title":"Haze Removal from Single Images Based on a Luminance Reference Model","authors":"Jiafeng Li, Hong Zhang, Ding Yuan, Helong Wang","doi":"10.1109/ACPR.2013.119","DOIUrl":null,"url":null,"abstract":"Optical transmission estimation is a key procedure for removing haze from certain outdoor images. In this paper, we propose a novel transmission estimation model called the luminance reference model. A luminance reference, which is the intensity lower bound of a local region in the haze free image, is assumed to be a global constant across the image. Based on this assumption, we theoretically prove that, with an appropriate luminance reference, the transmission can be estimated accurately. By using a scene-dependent estimate of the luminance reference, our method can be applied to different types of images. We further propose a two-step guided approach to rapid and robust computation of a transmission map. Our experimental results show that the proposed method is computationally efficient, while producing comparable visual results to the existing state-of-the-art, but more complex methods.","PeriodicalId":365633,"journal":{"name":"2013 2nd IAPR Asian Conference on Pattern Recognition","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 2nd IAPR Asian Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPR.2013.119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Optical transmission estimation is a key procedure for removing haze from certain outdoor images. In this paper, we propose a novel transmission estimation model called the luminance reference model. A luminance reference, which is the intensity lower bound of a local region in the haze free image, is assumed to be a global constant across the image. Based on this assumption, we theoretically prove that, with an appropriate luminance reference, the transmission can be estimated accurately. By using a scene-dependent estimate of the luminance reference, our method can be applied to different types of images. We further propose a two-step guided approach to rapid and robust computation of a transmission map. Our experimental results show that the proposed method is computationally efficient, while producing comparable visual results to the existing state-of-the-art, but more complex methods.