{"title":"多媒体大数据时代一种有效的雾图像采集算法","authors":"Jinxing Niu, Hengcan Li","doi":"10.1504/IJRIS.2018.10012212","DOIUrl":null,"url":null,"abstract":"Outdoor images are often degraded by fog weather conditions in the era of multimedia big data, which affect computer vision applications severely. In this paper, an effective fog image acquisition algorithm based on big data analysis is proposed in the big data environment, and single image defogging algorithm based on histogram equalisation and dark channel prior methods is proposed. The transmission and air light of the fog image need to be estimated by the dark channel prior theory methods, and then clear images can be received after defogging and keep the original colour. The experimental results show that the image by fog removal dark channel prior method can get clear images and keep the original colour, the treatment effect is better than that of the histogram equalisation method.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An effective foggy image acquisition algorithm in multimedia big data era\",\"authors\":\"Jinxing Niu, Hengcan Li\",\"doi\":\"10.1504/IJRIS.2018.10012212\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Outdoor images are often degraded by fog weather conditions in the era of multimedia big data, which affect computer vision applications severely. In this paper, an effective fog image acquisition algorithm based on big data analysis is proposed in the big data environment, and single image defogging algorithm based on histogram equalisation and dark channel prior methods is proposed. The transmission and air light of the fog image need to be estimated by the dark channel prior theory methods, and then clear images can be received after defogging and keep the original colour. The experimental results show that the image by fog removal dark channel prior method can get clear images and keep the original colour, the treatment effect is better than that of the histogram equalisation method.\",\"PeriodicalId\":360794,\"journal\":{\"name\":\"Int. J. Reason. based Intell. Syst.\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Reason. based Intell. Syst.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJRIS.2018.10012212\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Reason. based Intell. Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJRIS.2018.10012212","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An effective foggy image acquisition algorithm in multimedia big data era
Outdoor images are often degraded by fog weather conditions in the era of multimedia big data, which affect computer vision applications severely. In this paper, an effective fog image acquisition algorithm based on big data analysis is proposed in the big data environment, and single image defogging algorithm based on histogram equalisation and dark channel prior methods is proposed. The transmission and air light of the fog image need to be estimated by the dark channel prior theory methods, and then clear images can be received after defogging and keep the original colour. The experimental results show that the image by fog removal dark channel prior method can get clear images and keep the original colour, the treatment effect is better than that of the histogram equalisation method.