{"title":"基于分割的高分辨率图像半自动建筑物提取","authors":"N. Jiang, J. Zhang, H. T. Li, Xiangguo Lin","doi":"10.1109/EORSA.2008.4620311","DOIUrl":null,"url":null,"abstract":"Recently, more and more high resolution remote sensing images appear, and they provide new data source for building extraction. Some building extraction methods are proposed to adapt to this trend. This paper addresses a semi-automatic method that combines segmentation and region selection. First, mean shift segmentation is applied to the image, and then the region extraction is implemented through the interactively selection of building parts. Edge detection is also involved to get the boundary of buildings. At last, the paper gives the contrast of the unsupervised classification ISODATA result and this extraction method.","PeriodicalId":142612,"journal":{"name":"2008 International Workshop on Earth Observation and Remote Sensing Applications","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"Semi-automatic building extraction from high resolution imagery based on segmentation\",\"authors\":\"N. Jiang, J. Zhang, H. T. Li, Xiangguo Lin\",\"doi\":\"10.1109/EORSA.2008.4620311\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, more and more high resolution remote sensing images appear, and they provide new data source for building extraction. Some building extraction methods are proposed to adapt to this trend. This paper addresses a semi-automatic method that combines segmentation and region selection. First, mean shift segmentation is applied to the image, and then the region extraction is implemented through the interactively selection of building parts. Edge detection is also involved to get the boundary of buildings. At last, the paper gives the contrast of the unsupervised classification ISODATA result and this extraction method.\",\"PeriodicalId\":142612,\"journal\":{\"name\":\"2008 International Workshop on Earth Observation and Remote Sensing Applications\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Workshop on Earth Observation and Remote Sensing Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EORSA.2008.4620311\",\"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 International Workshop on Earth Observation and Remote Sensing Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EORSA.2008.4620311","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Semi-automatic building extraction from high resolution imagery based on segmentation
Recently, more and more high resolution remote sensing images appear, and they provide new data source for building extraction. Some building extraction methods are proposed to adapt to this trend. This paper addresses a semi-automatic method that combines segmentation and region selection. First, mean shift segmentation is applied to the image, and then the region extraction is implemented through the interactively selection of building parts. Edge detection is also involved to get the boundary of buildings. At last, the paper gives the contrast of the unsupervised classification ISODATA result and this extraction method.