Dongyang Li, Guiying Tang, Li Zhao, Xiaoqin Zhang, X. Ye
{"title":"Single I mage Haze Removal Based on Concentration Scale Prior","authors":"Dongyang Li, Guiying Tang, Li Zhao, Xiaoqin Zhang, X. Ye","doi":"10.1109/ICCCS49078.2020.9118551","DOIUrl":null,"url":null,"abstract":"Haze is a major degradation factor in outdoor images. Removing haze from a single image is an ill-posed problem and the performance of existing prior-based image dehazing methods is limited by the effectiveness of hand-designed features. In this paper, new dehazing method is introduced which is refined using gamma transformation and does not utilize the traditional atmospheric scattering model. The proposed method restores haze-free images without reference to corresponding clear image or estimating a depth-dependent transmission map. A novel, simple and powerful Concentration Scale Prior (CSP) is then utilized for haze removal in a single haze image to enhance gamma transformation, and its performance is verified. Experimental results show that the proposed approach achieves superior dehazing performance compared to current state-of-the-art methods.","PeriodicalId":105556,"journal":{"name":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Computer and Communication Systems (ICCCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCS49078.2020.9118551","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Haze is a major degradation factor in outdoor images. Removing haze from a single image is an ill-posed problem and the performance of existing prior-based image dehazing methods is limited by the effectiveness of hand-designed features. In this paper, new dehazing method is introduced which is refined using gamma transformation and does not utilize the traditional atmospheric scattering model. The proposed method restores haze-free images without reference to corresponding clear image or estimating a depth-dependent transmission map. A novel, simple and powerful Concentration Scale Prior (CSP) is then utilized for haze removal in a single haze image to enhance gamma transformation, and its performance is verified. Experimental results show that the proposed approach achieves superior dehazing performance compared to current state-of-the-art methods.