{"title":"基于一维插值的正方形到六边形晶格转换","authors":"Xiangguo Li, B. Gardiner, S. Coleman","doi":"10.1109/IPTA.2016.7821035","DOIUrl":null,"url":null,"abstract":"This paper concerns the square lattice to hexagonal lattice conversion in practical hexagonal image processing, and presents a simplified conversion method that converts the common two-dimensional (2-D) interpolation approach to one-dimensional (1-D) interpolation. This paper is motivated by the sampling interval relationship between the square lattice and the hexagonal lattice, and assumes the 2-D interpolation kernel as separable, then changes the 2-D interpolation into successive 1-D interpolations, and finally reduces to the 1-D interpolation along the horizontal direction only. Compared with the common 2-D interpolation approach, the proposed simplified conversion method is more simple and more computationally efficient, and it is also more suitable for parallel processing. Finally, the experimental results verify the correctness as well as the computational efficiency.","PeriodicalId":123429,"journal":{"name":"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Square to hexagonal lattice conversion based on one-dimensional interpolation\",\"authors\":\"Xiangguo Li, B. Gardiner, S. Coleman\",\"doi\":\"10.1109/IPTA.2016.7821035\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper concerns the square lattice to hexagonal lattice conversion in practical hexagonal image processing, and presents a simplified conversion method that converts the common two-dimensional (2-D) interpolation approach to one-dimensional (1-D) interpolation. This paper is motivated by the sampling interval relationship between the square lattice and the hexagonal lattice, and assumes the 2-D interpolation kernel as separable, then changes the 2-D interpolation into successive 1-D interpolations, and finally reduces to the 1-D interpolation along the horizontal direction only. Compared with the common 2-D interpolation approach, the proposed simplified conversion method is more simple and more computationally efficient, and it is also more suitable for parallel processing. Finally, the experimental results verify the correctness as well as the computational efficiency.\",\"PeriodicalId\":123429,\"journal\":{\"name\":\"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPTA.2016.7821035\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTA.2016.7821035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Square to hexagonal lattice conversion based on one-dimensional interpolation
This paper concerns the square lattice to hexagonal lattice conversion in practical hexagonal image processing, and presents a simplified conversion method that converts the common two-dimensional (2-D) interpolation approach to one-dimensional (1-D) interpolation. This paper is motivated by the sampling interval relationship between the square lattice and the hexagonal lattice, and assumes the 2-D interpolation kernel as separable, then changes the 2-D interpolation into successive 1-D interpolations, and finally reduces to the 1-D interpolation along the horizontal direction only. Compared with the common 2-D interpolation approach, the proposed simplified conversion method is more simple and more computationally efficient, and it is also more suitable for parallel processing. Finally, the experimental results verify the correctness as well as the computational efficiency.