{"title":"基于匹配的高光去除","authors":"Yiren Xu, Fujian Wang, Yuming Zhao","doi":"10.1109/ICMULT.2010.5631281","DOIUrl":null,"url":null,"abstract":"This paper presents a three-step framework to remove the highlight exists on objects in certain conditions. Unlike traditional HDR (High Dynamic Range) technology requires multiple registrated image sequence; our method needs only two arbitrary images. SURF (Speeded Up Robust Features) matching algorithm is first applied to find corresponding point pairs between images; homography is then found by perspective transformation theory; minimum gray selection is used at last to eliminated the highlight and fuse related regions. Experimental results are given to demonstrate the performance of our method.","PeriodicalId":412601,"journal":{"name":"2010 International Conference on Multimedia Technology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Matching based Highlight Removal\",\"authors\":\"Yiren Xu, Fujian Wang, Yuming Zhao\",\"doi\":\"10.1109/ICMULT.2010.5631281\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a three-step framework to remove the highlight exists on objects in certain conditions. Unlike traditional HDR (High Dynamic Range) technology requires multiple registrated image sequence; our method needs only two arbitrary images. SURF (Speeded Up Robust Features) matching algorithm is first applied to find corresponding point pairs between images; homography is then found by perspective transformation theory; minimum gray selection is used at last to eliminated the highlight and fuse related regions. Experimental results are given to demonstrate the performance of our method.\",\"PeriodicalId\":412601,\"journal\":{\"name\":\"2010 International Conference on Multimedia Technology\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Multimedia Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMULT.2010.5631281\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Multimedia Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMULT.2010.5631281","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a three-step framework to remove the highlight exists on objects in certain conditions. Unlike traditional HDR (High Dynamic Range) technology requires multiple registrated image sequence; our method needs only two arbitrary images. SURF (Speeded Up Robust Features) matching algorithm is first applied to find corresponding point pairs between images; homography is then found by perspective transformation theory; minimum gray selection is used at last to eliminated the highlight and fuse related regions. Experimental results are given to demonstrate the performance of our method.