{"title":"使用色彩通道相关性校正过度曝光","authors":"M. Abebe, T. Pouli, J. Kervec, M. Larabi","doi":"10.1109/GlobalSIP.2014.7032287","DOIUrl":null,"url":null,"abstract":"We present a new method for correcting over-exposed areas in images. The method takes advantage of the strong correlation between the RGB color channels and relies on the observation that in images the RGB components are often not over-exposed at the same position. Our solution operates on line profiles, making it ideally suited for hardware implementations. In addition to its low computational complexity, our method can accurately recover information in areas where one or two channels are over-exposed, while it reconstructs information in areas that are fully clipped. We show that our method outperforms previous algorithms through quantitative analysis and we demonstrate an important application of this type of solution in the context of high dynamic range image reconstruction.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Correction of over-exposure using color channel correlations\",\"authors\":\"M. Abebe, T. Pouli, J. Kervec, M. Larabi\",\"doi\":\"10.1109/GlobalSIP.2014.7032287\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a new method for correcting over-exposed areas in images. The method takes advantage of the strong correlation between the RGB color channels and relies on the observation that in images the RGB components are often not over-exposed at the same position. Our solution operates on line profiles, making it ideally suited for hardware implementations. In addition to its low computational complexity, our method can accurately recover information in areas where one or two channels are over-exposed, while it reconstructs information in areas that are fully clipped. We show that our method outperforms previous algorithms through quantitative analysis and we demonstrate an important application of this type of solution in the context of high dynamic range image reconstruction.\",\"PeriodicalId\":362306,\"journal\":{\"name\":\"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GlobalSIP.2014.7032287\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobalSIP.2014.7032287","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Correction of over-exposure using color channel correlations
We present a new method for correcting over-exposed areas in images. The method takes advantage of the strong correlation between the RGB color channels and relies on the observation that in images the RGB components are often not over-exposed at the same position. Our solution operates on line profiles, making it ideally suited for hardware implementations. In addition to its low computational complexity, our method can accurately recover information in areas where one or two channels are over-exposed, while it reconstructs information in areas that are fully clipped. We show that our method outperforms previous algorithms through quantitative analysis and we demonstrate an important application of this type of solution in the context of high dynamic range image reconstruction.