{"title":"用高斯函数和进行曲线拟合","authors":"Goshtasby A., Oneill W.D.","doi":"10.1006/cgip.1994.1025","DOIUrl":null,"url":null,"abstract":"<div><p>Gaussians are useful in multiscale representation of video data. An algorithm is presented which approximates a sequence of uniformly spaced single-valued data by a sum of Gaussians with a prescribed accuracy. The scale-space image [6] of the data is used to estimate the number of Gaussians and their initial parameters. The Marquardt algorithm (<em>J. SIAM</em> 11(2), 1963, 431-441) is then used to optimize the parameters.</p></div>","PeriodicalId":100349,"journal":{"name":"CVGIP: Graphical Models and Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1994-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/cgip.1994.1025","citationCount":"86","resultStr":"{\"title\":\"Curve Fitting by a Sum of Gaussians\",\"authors\":\"Goshtasby A., Oneill W.D.\",\"doi\":\"10.1006/cgip.1994.1025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Gaussians are useful in multiscale representation of video data. An algorithm is presented which approximates a sequence of uniformly spaced single-valued data by a sum of Gaussians with a prescribed accuracy. The scale-space image [6] of the data is used to estimate the number of Gaussians and their initial parameters. The Marquardt algorithm (<em>J. SIAM</em> 11(2), 1963, 431-441) is then used to optimize the parameters.</p></div>\",\"PeriodicalId\":100349,\"journal\":{\"name\":\"CVGIP: Graphical Models and Image Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1006/cgip.1994.1025\",\"citationCount\":\"86\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CVGIP: Graphical Models and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S104996528471025X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CVGIP: Graphical Models and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S104996528471025X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Gaussians are useful in multiscale representation of video data. An algorithm is presented which approximates a sequence of uniformly spaced single-valued data by a sum of Gaussians with a prescribed accuracy. The scale-space image [6] of the data is used to estimate the number of Gaussians and their initial parameters. The Marquardt algorithm (J. SIAM 11(2), 1963, 431-441) is then used to optimize the parameters.
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