{"title":"基于patch的图像去噪结构自适应","authors":"Xiaofeng Du, Cuihua Li, Dunxu Yang","doi":"10.1109/CAR.2009.111","DOIUrl":null,"url":null,"abstract":"Most existing patch-based denoising methods are based on fixed size patch and fixed range of neighborhood, while producing state-of-the-art denoising results, the quality of the algorithm is significantly dependent on patch size. Suppose that patch size is related to image pattern, a structural adaption method for the selection of patch size is proposed in this paper. Due to the mutual similaritybetween the training samples, the simulation results illustrate the original approach can be effectively improved by adopted this method.","PeriodicalId":320307,"journal":{"name":"2009 International Asia Conference on Informatics in Control, Automation and Robotics","volume":"244 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Structural Adaptation for Patch-Based Image Denoising\",\"authors\":\"Xiaofeng Du, Cuihua Li, Dunxu Yang\",\"doi\":\"10.1109/CAR.2009.111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most existing patch-based denoising methods are based on fixed size patch and fixed range of neighborhood, while producing state-of-the-art denoising results, the quality of the algorithm is significantly dependent on patch size. Suppose that patch size is related to image pattern, a structural adaption method for the selection of patch size is proposed in this paper. Due to the mutual similaritybetween the training samples, the simulation results illustrate the original approach can be effectively improved by adopted this method.\",\"PeriodicalId\":320307,\"journal\":{\"name\":\"2009 International Asia Conference on Informatics in Control, Automation and Robotics\",\"volume\":\"244 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Asia Conference on Informatics in Control, Automation and Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAR.2009.111\",\"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 International Asia Conference on Informatics in Control, Automation and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAR.2009.111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Structural Adaptation for Patch-Based Image Denoising
Most existing patch-based denoising methods are based on fixed size patch and fixed range of neighborhood, while producing state-of-the-art denoising results, the quality of the algorithm is significantly dependent on patch size. Suppose that patch size is related to image pattern, a structural adaption method for the selection of patch size is proposed in this paper. Due to the mutual similaritybetween the training samples, the simulation results illustrate the original approach can be effectively improved by adopted this method.