{"title":"利用几何对偶的定向线插值","authors":"Sang-Jun Park, Jechang Jeong, Gwanggil Jeon","doi":"10.1109/DICTA.2010.24","DOIUrl":null,"url":null,"abstract":"In this paper, a direction-oriented covariance based deinterlacing method is presented. First, the local direction of edge is determined by modified edge-based line average (MELA) method. Then, based on the geometric duality, the optimal interpolation coefficients for the neighbor pixels of corresponding direction are estimated using the Wiener filtering. Experimental results prove that the proposed method provides a significant improvement over the other existing deinterlacing methods.","PeriodicalId":246460,"journal":{"name":"2010 International Conference on Digital Image Computing: Techniques and Applications","volume":"144 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Direction-Oriented Line Interpolation Using Geometric Duality\",\"authors\":\"Sang-Jun Park, Jechang Jeong, Gwanggil Jeon\",\"doi\":\"10.1109/DICTA.2010.24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a direction-oriented covariance based deinterlacing method is presented. First, the local direction of edge is determined by modified edge-based line average (MELA) method. Then, based on the geometric duality, the optimal interpolation coefficients for the neighbor pixels of corresponding direction are estimated using the Wiener filtering. Experimental results prove that the proposed method provides a significant improvement over the other existing deinterlacing methods.\",\"PeriodicalId\":246460,\"journal\":{\"name\":\"2010 International Conference on Digital Image Computing: Techniques and Applications\",\"volume\":\"144 5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Digital Image Computing: Techniques and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DICTA.2010.24\",\"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 Digital Image Computing: Techniques and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA.2010.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Direction-Oriented Line Interpolation Using Geometric Duality
In this paper, a direction-oriented covariance based deinterlacing method is presented. First, the local direction of edge is determined by modified edge-based line average (MELA) method. Then, based on the geometric duality, the optimal interpolation coefficients for the neighbor pixels of corresponding direction are estimated using the Wiener filtering. Experimental results prove that the proposed method provides a significant improvement over the other existing deinterlacing methods.