{"title":"向量数学形态学的聚类方法","authors":"C. Vertan, M. Malciu, T. Zaharia, V. Buzuloiu","doi":"10.1109/ICECS.1996.582749","DOIUrl":null,"url":null,"abstract":"The processing and analysis of vector valued signals has become in the last decade a major field of interest. The direct extension of classical processing methods for the scalar signals is not always possible. The mathematical morphology viewed as a processing technique for gray images is such that it cannot be extended easily. In this paper we present an approach to the vector mathematical morphology based on clustering techniques in the signal sample space.","PeriodicalId":402369,"journal":{"name":"Proceedings of Third International Conference on Electronics, Circuits, and Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A clustering approach to vector mathematical morphology\",\"authors\":\"C. Vertan, M. Malciu, T. Zaharia, V. Buzuloiu\",\"doi\":\"10.1109/ICECS.1996.582749\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The processing and analysis of vector valued signals has become in the last decade a major field of interest. The direct extension of classical processing methods for the scalar signals is not always possible. The mathematical morphology viewed as a processing technique for gray images is such that it cannot be extended easily. In this paper we present an approach to the vector mathematical morphology based on clustering techniques in the signal sample space.\",\"PeriodicalId\":402369,\"journal\":{\"name\":\"Proceedings of Third International Conference on Electronics, Circuits, and Systems\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of Third International Conference on Electronics, Circuits, and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECS.1996.582749\",\"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 of Third International Conference on Electronics, Circuits, and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECS.1996.582749","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A clustering approach to vector mathematical morphology
The processing and analysis of vector valued signals has become in the last decade a major field of interest. The direct extension of classical processing methods for the scalar signals is not always possible. The mathematical morphology viewed as a processing technique for gray images is such that it cannot be extended easily. In this paper we present an approach to the vector mathematical morphology based on clustering techniques in the signal sample space.
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