{"title":"历史文献去噪研究","authors":"Guoming Chen, Qiang Chen, Xiongyong Zhu, Yiqun Chen","doi":"10.1109/CISP-BMEI.2017.8301947","DOIUrl":null,"url":null,"abstract":"In this paper we present a study on historical documents denoising methods and make visual quality performance comparison through Deep Residual Learning, Alternating Direction Method of Multiplier and Anisotropic diffusion PDE. Experimental results demonstrate their denoising visual quality performance and we make a comparison to in different condition respectively.","PeriodicalId":6474,"journal":{"name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"107 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A study of historical documents denoising\",\"authors\":\"Guoming Chen, Qiang Chen, Xiongyong Zhu, Yiqun Chen\",\"doi\":\"10.1109/CISP-BMEI.2017.8301947\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present a study on historical documents denoising methods and make visual quality performance comparison through Deep Residual Learning, Alternating Direction Method of Multiplier and Anisotropic diffusion PDE. Experimental results demonstrate their denoising visual quality performance and we make a comparison to in different condition respectively.\",\"PeriodicalId\":6474,\"journal\":{\"name\":\"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"volume\":\"107 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP-BMEI.2017.8301947\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI.2017.8301947","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we present a study on historical documents denoising methods and make visual quality performance comparison through Deep Residual Learning, Alternating Direction Method of Multiplier and Anisotropic diffusion PDE. Experimental results demonstrate their denoising visual quality performance and we make a comparison to in different condition respectively.