{"title":"基于马尔科夫随机场的显微镜离焦图像深度信息估计","authors":"Xiangjin Zeng, Xinhan Huang, Min Wang, Peng Li","doi":"10.1109/RAMECH.2008.4681326","DOIUrl":null,"url":null,"abstract":"For depth information estimation of microscope defocus image, a blur parameter model of defocus image based on Markov random field has been present. It converts problem of depth estimation into optimization problem. An improved iterated conditional modes algorithm has been applied to complete optimization problem, which the select of initial point employed least squares estimate algorithm prevents that the result gets into local optimization. The experiments and simulations prove that the model and algorithm is efficiency.","PeriodicalId":320560,"journal":{"name":"2008 IEEE Conference on Robotics, Automation and Mechatronics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Depth Information Estimation of Microscope Defocus Image Based-on Markov Random Field\",\"authors\":\"Xiangjin Zeng, Xinhan Huang, Min Wang, Peng Li\",\"doi\":\"10.1109/RAMECH.2008.4681326\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For depth information estimation of microscope defocus image, a blur parameter model of defocus image based on Markov random field has been present. It converts problem of depth estimation into optimization problem. An improved iterated conditional modes algorithm has been applied to complete optimization problem, which the select of initial point employed least squares estimate algorithm prevents that the result gets into local optimization. The experiments and simulations prove that the model and algorithm is efficiency.\",\"PeriodicalId\":320560,\"journal\":{\"name\":\"2008 IEEE Conference on Robotics, Automation and Mechatronics\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE Conference on Robotics, Automation and Mechatronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RAMECH.2008.4681326\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Conference on Robotics, Automation and Mechatronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RAMECH.2008.4681326","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Depth Information Estimation of Microscope Defocus Image Based-on Markov Random Field
For depth information estimation of microscope defocus image, a blur parameter model of defocus image based on Markov random field has been present. It converts problem of depth estimation into optimization problem. An improved iterated conditional modes algorithm has been applied to complete optimization problem, which the select of initial point employed least squares estimate algorithm prevents that the result gets into local optimization. The experiments and simulations prove that the model and algorithm is efficiency.