{"title":"CCD noise filtering based on surface diffusion model combined with min/max curvature","authors":"S. Lee, M. Kang, Kyu Tae Park","doi":"10.1109/ISCE.1997.658405","DOIUrl":null,"url":null,"abstract":"We propose to combine the min/max curvature to the surface diffusion model. The resulting technique is an automatic, extremely robust, computationally efficient, and a straightforward scheme. The flow under min/max curvature was presented by Malladi and Sethian (see Graphic. Models Image Processing, vol.58, no.2, p.127-141, 1996) in a differential equation in terms of the image intensity. If it is combined to the surface diffusion model then the new scheme automatically picks the termination criteria; continued application of the scheme produces no further change. In other words it has a convergence state. It has another important advantage over the MCD (mean curvature diffusion) and other diffusion models; removing notch noise on the side of a structure does not diffuse the shape of the structure.","PeriodicalId":393861,"journal":{"name":"ISCE '97. Proceedings of 1997 IEEE International Symposium on Consumer Electronics (Cat. No.97TH8348)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1997-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISCE '97. Proceedings of 1997 IEEE International Symposium on Consumer Electronics (Cat. No.97TH8348)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCE.1997.658405","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We propose to combine the min/max curvature to the surface diffusion model. The resulting technique is an automatic, extremely robust, computationally efficient, and a straightforward scheme. The flow under min/max curvature was presented by Malladi and Sethian (see Graphic. Models Image Processing, vol.58, no.2, p.127-141, 1996) in a differential equation in terms of the image intensity. If it is combined to the surface diffusion model then the new scheme automatically picks the termination criteria; continued application of the scheme produces no further change. In other words it has a convergence state. It has another important advantage over the MCD (mean curvature diffusion) and other diffusion models; removing notch noise on the side of a structure does not diffuse the shape of the structure.