{"title":"基于线性pde滤波模型的数字图像恢复","authors":"T. Barbu","doi":"10.56082/annalsarsciinfo.2022.1-2.45","DOIUrl":null,"url":null,"abstract":"The linear partial differential equation (PDE) - based models for Gaussian noise removal are discussed in this paper. The digital image denoising and restoration solutions based on linear diffusion equations are surveyed first. Then, our own contributions in this image processing domain, representing some effective linear PDE-based filtering models based on hyperbolic and stochastic differential equations, are presented. The results of our denoising experiments are also provided in this article.","PeriodicalId":32445,"journal":{"name":"Annals Series on History and Archaeology Academy of Romanian Scientists","volume":"27 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DIGITAL IMAGE RESTORATION USING LINEAR PDE-BASED FILTERING MODELS\",\"authors\":\"T. Barbu\",\"doi\":\"10.56082/annalsarsciinfo.2022.1-2.45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The linear partial differential equation (PDE) - based models for Gaussian noise removal are discussed in this paper. The digital image denoising and restoration solutions based on linear diffusion equations are surveyed first. Then, our own contributions in this image processing domain, representing some effective linear PDE-based filtering models based on hyperbolic and stochastic differential equations, are presented. The results of our denoising experiments are also provided in this article.\",\"PeriodicalId\":32445,\"journal\":{\"name\":\"Annals Series on History and Archaeology Academy of Romanian Scientists\",\"volume\":\"27 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals Series on History and Archaeology Academy of Romanian Scientists\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.56082/annalsarsciinfo.2022.1-2.45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals Series on History and Archaeology Academy of Romanian Scientists","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56082/annalsarsciinfo.2022.1-2.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DIGITAL IMAGE RESTORATION USING LINEAR PDE-BASED FILTERING MODELS
The linear partial differential equation (PDE) - based models for Gaussian noise removal are discussed in this paper. The digital image denoising and restoration solutions based on linear diffusion equations are surveyed first. Then, our own contributions in this image processing domain, representing some effective linear PDE-based filtering models based on hyperbolic and stochastic differential equations, are presented. The results of our denoising experiments are also provided in this article.