{"title":"基于闭周期区域的对称b样条图像放大","authors":"K. Zhou, Lixin Zheng, F. Lin","doi":"10.1109/ICICISYS.2009.5357740","DOIUrl":null,"url":null,"abstract":"Aiming at the weakness of ignoring symmetry property and using complicated iterative algorithms to solve for interpolation coefficients in the existing time domain B-spline interpolation methods, this paper presents a novel B-spline interpolation method using symmetric B-spline basis on closed periodic zone where interpolation coefficients can be fast computed by parallel algorithms. First we shift naïve B-spline basis to establish symmetric B-spline basis, next we use orthogonality properties of complex exponentials to establish orthogonal B-spline basis on closed periodic zone and derive parallel computing formula for coefficients of orthogonal Bspline basis; we further use relation between coefficients of orthogonal B-spline basis and coefficients of symmetric B-spline basis to achieve parallel computing formulas for interpolation coefficients of symmetric B-spline basis. At last, we extend the method to image enlargement. Experiment results show that, the new theory established in this paper can be used to explain result of B-spline interpolation from standpoint of signal processing. The method presented in this paper can easily carry out parallel computation for interpolation coefficients of symmetric B-spline basis and brings no phase deviation to enlarged image. Compared with neighborhood-based bilinear and bicubic interpolation methods, the new method produces enlargement with higher Peak Signal to Noise Ratio (PSNR) and sharper visual quality.","PeriodicalId":206575,"journal":{"name":"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Image enlargement using symmetric B-spline basis on closed periodic zone\",\"authors\":\"K. Zhou, Lixin Zheng, F. Lin\",\"doi\":\"10.1109/ICICISYS.2009.5357740\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the weakness of ignoring symmetry property and using complicated iterative algorithms to solve for interpolation coefficients in the existing time domain B-spline interpolation methods, this paper presents a novel B-spline interpolation method using symmetric B-spline basis on closed periodic zone where interpolation coefficients can be fast computed by parallel algorithms. First we shift naïve B-spline basis to establish symmetric B-spline basis, next we use orthogonality properties of complex exponentials to establish orthogonal B-spline basis on closed periodic zone and derive parallel computing formula for coefficients of orthogonal Bspline basis; we further use relation between coefficients of orthogonal B-spline basis and coefficients of symmetric B-spline basis to achieve parallel computing formulas for interpolation coefficients of symmetric B-spline basis. At last, we extend the method to image enlargement. Experiment results show that, the new theory established in this paper can be used to explain result of B-spline interpolation from standpoint of signal processing. The method presented in this paper can easily carry out parallel computation for interpolation coefficients of symmetric B-spline basis and brings no phase deviation to enlarged image. Compared with neighborhood-based bilinear and bicubic interpolation methods, the new method produces enlargement with higher Peak Signal to Noise Ratio (PSNR) and sharper visual quality.\",\"PeriodicalId\":206575,\"journal\":{\"name\":\"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICISYS.2009.5357740\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICISYS.2009.5357740","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image enlargement using symmetric B-spline basis on closed periodic zone
Aiming at the weakness of ignoring symmetry property and using complicated iterative algorithms to solve for interpolation coefficients in the existing time domain B-spline interpolation methods, this paper presents a novel B-spline interpolation method using symmetric B-spline basis on closed periodic zone where interpolation coefficients can be fast computed by parallel algorithms. First we shift naïve B-spline basis to establish symmetric B-spline basis, next we use orthogonality properties of complex exponentials to establish orthogonal B-spline basis on closed periodic zone and derive parallel computing formula for coefficients of orthogonal Bspline basis; we further use relation between coefficients of orthogonal B-spline basis and coefficients of symmetric B-spline basis to achieve parallel computing formulas for interpolation coefficients of symmetric B-spline basis. At last, we extend the method to image enlargement. Experiment results show that, the new theory established in this paper can be used to explain result of B-spline interpolation from standpoint of signal processing. The method presented in this paper can easily carry out parallel computation for interpolation coefficients of symmetric B-spline basis and brings no phase deviation to enlarged image. Compared with neighborhood-based bilinear and bicubic interpolation methods, the new method produces enlargement with higher Peak Signal to Noise Ratio (PSNR) and sharper visual quality.