{"title":"利用互信息匹配点特征","authors":"A. Rangarajan, J. S. Duncan","doi":"10.1109/BIA.1998.692445","DOIUrl":null,"url":null,"abstract":"The authors have developed a new mutual information-based registration method for matching unlabeled point features. In contrast to earlier mutual information-based registration methods which estimate the mutual information using image intensity information, the authors' approach uses the point feature location information. A novel aspect of their approach is the spontaneous emergence of correspondence (between the two sets of features) as a natural by-product of information maximization. The authors have applied this algorithm to the problem of geometric alignment of primate autoradiographs. They also present a detailed theoretical comparison between their approach and other approaches that explicitly parameterize feature correspondence.","PeriodicalId":261632,"journal":{"name":"Proceedings. Workshop on Biomedical Image Analysis (Cat. No.98EX162)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Matching point features using mutual information\",\"authors\":\"A. Rangarajan, J. S. Duncan\",\"doi\":\"10.1109/BIA.1998.692445\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors have developed a new mutual information-based registration method for matching unlabeled point features. In contrast to earlier mutual information-based registration methods which estimate the mutual information using image intensity information, the authors' approach uses the point feature location information. A novel aspect of their approach is the spontaneous emergence of correspondence (between the two sets of features) as a natural by-product of information maximization. The authors have applied this algorithm to the problem of geometric alignment of primate autoradiographs. They also present a detailed theoretical comparison between their approach and other approaches that explicitly parameterize feature correspondence.\",\"PeriodicalId\":261632,\"journal\":{\"name\":\"Proceedings. Workshop on Biomedical Image Analysis (Cat. No.98EX162)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. Workshop on Biomedical Image Analysis (Cat. No.98EX162)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIA.1998.692445\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. Workshop on Biomedical Image Analysis (Cat. No.98EX162)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIA.1998.692445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The authors have developed a new mutual information-based registration method for matching unlabeled point features. In contrast to earlier mutual information-based registration methods which estimate the mutual information using image intensity information, the authors' approach uses the point feature location information. A novel aspect of their approach is the spontaneous emergence of correspondence (between the two sets of features) as a natural by-product of information maximization. The authors have applied this algorithm to the problem of geometric alignment of primate autoradiographs. They also present a detailed theoretical comparison between their approach and other approaches that explicitly parameterize feature correspondence.