{"title":"一种亚像素多重分形图像分割方法","authors":"G. Wang, Liang Xiao, Anzhi He","doi":"10.1109/FSKD.2007.126","DOIUrl":null,"url":null,"abstract":"The framework of image segmentation based on the sub-pixel multifractal measure (SPMM) is presented in this paper. A more precise singularity exponent distribution in the image can be obtained based on the SPMM. According to the singularity exponents and their statistical properties, the image can be decomposed into a series of sets with different physical characteristics automatically and easily. Moreover, the most singular manifold can be interpreted as the set from which energy is injected in the flow to the other fractal sets. The simulation results show that the SPMM has higher quality factor in the image edge detection.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"44 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Sub-pixel Multifractal Method for the Image Segmentation\",\"authors\":\"G. Wang, Liang Xiao, Anzhi He\",\"doi\":\"10.1109/FSKD.2007.126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The framework of image segmentation based on the sub-pixel multifractal measure (SPMM) is presented in this paper. A more precise singularity exponent distribution in the image can be obtained based on the SPMM. According to the singularity exponents and their statistical properties, the image can be decomposed into a series of sets with different physical characteristics automatically and easily. Moreover, the most singular manifold can be interpreted as the set from which energy is injected in the flow to the other fractal sets. The simulation results show that the SPMM has higher quality factor in the image edge detection.\",\"PeriodicalId\":201883,\"journal\":{\"name\":\"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)\",\"volume\":\"44 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FSKD.2007.126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FSKD.2007.126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Sub-pixel Multifractal Method for the Image Segmentation
The framework of image segmentation based on the sub-pixel multifractal measure (SPMM) is presented in this paper. A more precise singularity exponent distribution in the image can be obtained based on the SPMM. According to the singularity exponents and their statistical properties, the image can be decomposed into a series of sets with different physical characteristics automatically and easily. Moreover, the most singular manifold can be interpreted as the set from which energy is injected in the flow to the other fractal sets. The simulation results show that the SPMM has higher quality factor in the image edge detection.