{"title":"历史文献图像的自适应增强","authors":"N. Kishore, P. Rege","doi":"10.1109/ISSPIT.2007.4458058","DOIUrl":null,"url":null,"abstract":"In this paper we present a simple and computationally efficient method for document image enhancement. We use Unsharp masking to enhance the edge detail information in the degraded document. This image is then used to adjust the local threshold for each pixel. Proposed method is experimentally compared with Laplacian sign method and the Otsu method. It is shown that the method improves sharpness of the image with nearly half computational time.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Adaptive Enhancement of Historical Document Images\",\"authors\":\"N. Kishore, P. Rege\",\"doi\":\"10.1109/ISSPIT.2007.4458058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present a simple and computationally efficient method for document image enhancement. We use Unsharp masking to enhance the edge detail information in the degraded document. This image is then used to adjust the local threshold for each pixel. Proposed method is experimentally compared with Laplacian sign method and the Otsu method. It is shown that the method improves sharpness of the image with nearly half computational time.\",\"PeriodicalId\":299267,\"journal\":{\"name\":\"2007 IEEE International Symposium on Signal Processing and Information Technology\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE International Symposium on Signal Processing and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPIT.2007.4458058\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Symposium on Signal Processing and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT.2007.4458058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Enhancement of Historical Document Images
In this paper we present a simple and computationally efficient method for document image enhancement. We use Unsharp masking to enhance the edge detail information in the degraded document. This image is then used to adjust the local threshold for each pixel. Proposed method is experimentally compared with Laplacian sign method and the Otsu method. It is shown that the method improves sharpness of the image with nearly half computational time.