{"title":"Image coupling, restoration and enhancement via PDE's","authors":"Pierre Kornprobst, R. Deriche, G. Aubert","doi":"10.1109/ICIP.1997.638807","DOIUrl":null,"url":null,"abstract":"We present a new approach based on partial differential equations (PDE) to restore noisy blurred images. After studying the methods to denoise images, staying as close as possible to the input image and methods to restore discontinuities, we propose a new scheme which combines all this schemes. A quantified numerical test on a synthetic image demonstrates the efficiency of our scheme and the role of varying the parameters for denoising, enhancement and coupling. A result on a real image is also presented.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"103 1","pages":"458-461 vol.2"},"PeriodicalIF":0.0000,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"87","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.1997.638807","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 87

Abstract

We present a new approach based on partial differential equations (PDE) to restore noisy blurred images. After studying the methods to denoise images, staying as close as possible to the input image and methods to restore discontinuities, we propose a new scheme which combines all this schemes. A quantified numerical test on a synthetic image demonstrates the efficiency of our scheme and the role of varying the parameters for denoising, enhancement and coupling. A result on a real image is also presented.
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通过PDE的图像耦合,恢复和增强
提出了一种基于偏微分方程(PDE)的图像复原方法。在研究了图像去噪、尽可能接近输入图像和恢复不连续点的方法后,提出了一种综合上述方法的新方案。通过对合成图像的量化数值实验,验证了该方法的有效性,以及改变参数对去噪、增强和耦合的作用。并给出了实际图像上的结果。
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Computer Analysis of Images and Patterns: 19th International Conference, CAIP 2021, Virtual Event, September 28–30, 2021, Proceedings, Part I Computer Analysis of Images and Patterns: 19th International Conference, CAIP 2021, Virtual Event, September 28–30, 2021, Proceedings, Part II Computer Analysis of Images and Patterns: CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings Computer Analysis of Images and Patterns: 18th International Conference, CAIP 2019, Salerno, Italy, September 3–5, 2019, Proceedings, Part I Computer Analysis of Images and Patterns: 18th International Conference, CAIP 2019, Salerno, Italy, September 3–5, 2019, Proceedings, Part II
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