Jiajie Liu, Jieying Zheng, Z. Cui, Guijin Tang, Feng Liu
{"title":"An improved image dehazing algorithm based on dark channel prior","authors":"Jiajie Liu, Jieying Zheng, Z. Cui, Guijin Tang, Feng Liu","doi":"10.1109/WARTIA.2014.6976545","DOIUrl":null,"url":null,"abstract":"Image dehazing algorithm based on dark channel prior has been proved to be effective, but it cannot still guarantee accurate transmission. To solve this problem, we firstly propose a more reasonable estimation of atmospheric light, because bias in the atmospheric light estimation will cause an inaccurate transmission. Secondly, we improve the estimation of transmission in bright area so as to alleviate color distortion. After image recovery, we carry out denoising to improve the image quality. Finally, we use a blind image quality assessment method based on property of Human Visual System, and the experimental results show that this improved algorithm is more effective.","PeriodicalId":288854,"journal":{"name":"2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WARTIA.2014.6976545","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Image dehazing algorithm based on dark channel prior has been proved to be effective, but it cannot still guarantee accurate transmission. To solve this problem, we firstly propose a more reasonable estimation of atmospheric light, because bias in the atmospheric light estimation will cause an inaccurate transmission. Secondly, we improve the estimation of transmission in bright area so as to alleviate color distortion. After image recovery, we carry out denoising to improve the image quality. Finally, we use a blind image quality assessment method based on property of Human Visual System, and the experimental results show that this improved algorithm is more effective.
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