{"title":"一种新的基于图像特征的偏微分方程方法及其在去噪中的应用","authors":"A. A. Yahya, Jieqing Tan","doi":"10.1109/ICDH.2012.36","DOIUrl":null,"url":null,"abstract":"In this paper a novel denoising algorithm based on partial differential equation variational approach is proposed. The proposed algorithm is obtained by weighted combinations of the an isotropic diffusion model and total variation model. Experimental results show that our new approach is more efficient in image denoising than both an isotropic diffusion and total variation in terms of preserving edges information and texture features.","PeriodicalId":308799,"journal":{"name":"2012 Fourth International Conference on Digital Home","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A Novel Partial Differential Equation Method Based on Image Features and Its Applications in Denoising\",\"authors\":\"A. A. Yahya, Jieqing Tan\",\"doi\":\"10.1109/ICDH.2012.36\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a novel denoising algorithm based on partial differential equation variational approach is proposed. The proposed algorithm is obtained by weighted combinations of the an isotropic diffusion model and total variation model. Experimental results show that our new approach is more efficient in image denoising than both an isotropic diffusion and total variation in terms of preserving edges information and texture features.\",\"PeriodicalId\":308799,\"journal\":{\"name\":\"2012 Fourth International Conference on Digital Home\",\"volume\":\"82 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fourth International Conference on Digital Home\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDH.2012.36\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fourth International Conference on Digital Home","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDH.2012.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Partial Differential Equation Method Based on Image Features and Its Applications in Denoising
In this paper a novel denoising algorithm based on partial differential equation variational approach is proposed. The proposed algorithm is obtained by weighted combinations of the an isotropic diffusion model and total variation model. Experimental results show that our new approach is more efficient in image denoising than both an isotropic diffusion and total variation in terms of preserving edges information and texture features.