{"title":"噪声图像的组合边缘检测算法","authors":"S. Rital, A. Bretto, H. Cherifi, D. Aboutajdine","doi":"10.1109/VIPROM.2002.1026681","DOIUrl":null,"url":null,"abstract":"In this paper, we present an algorithm for edge detection in noisy images. First, an image adaptive neighborhood hypergraph (IANH) representation is computed. Next, a detection procedure based on hypergraph properties is used to classify hyperedges either as noise, edges or region. The application of this technique to noisy images has resulted in a considerable improvement in performance as compared to classical approaches.","PeriodicalId":223771,"journal":{"name":"International Symposium on VIPromCom Video/Image Processing and Multimedia Communications","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"A combinatorial edge detection algorithm on noisy images\",\"authors\":\"S. Rital, A. Bretto, H. Cherifi, D. Aboutajdine\",\"doi\":\"10.1109/VIPROM.2002.1026681\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present an algorithm for edge detection in noisy images. First, an image adaptive neighborhood hypergraph (IANH) representation is computed. Next, a detection procedure based on hypergraph properties is used to classify hyperedges either as noise, edges or region. The application of this technique to noisy images has resulted in a considerable improvement in performance as compared to classical approaches.\",\"PeriodicalId\":223771,\"journal\":{\"name\":\"International Symposium on VIPromCom Video/Image Processing and Multimedia Communications\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on VIPromCom Video/Image Processing and Multimedia Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VIPROM.2002.1026681\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on VIPromCom Video/Image Processing and Multimedia Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VIPROM.2002.1026681","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A combinatorial edge detection algorithm on noisy images
In this paper, we present an algorithm for edge detection in noisy images. First, an image adaptive neighborhood hypergraph (IANH) representation is computed. Next, a detection procedure based on hypergraph properties is used to classify hyperedges either as noise, edges or region. The application of this technique to noisy images has resulted in a considerable improvement in performance as compared to classical approaches.
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