Jinxing Chen, Bo Zhang, Chao Wang, Hong Zhang, Fan Wu
{"title":"Building features extraction based on facade regularities using TerraSAR-X ST data","authors":"Jinxing Chen, Bo Zhang, Chao Wang, Hong Zhang, Fan Wu","doi":"10.1109/APSAR.2015.7306218","DOIUrl":null,"url":null,"abstract":"The grammar of facade structures is often related to regularly distributed signature patterns in high-resolution synthetic aperture radar (SAR) images. Given the structural details in the SAR image, algorithms for building extraction/monitoring should exploit this contextual information for an object-based analysis. In this paper we propose a framework to extract detailed high rise building features including building masks, orientations and stories. We developed a top-down approach which consists of processing at three levels, namely image level, region-of-interest (ROI) level and storey level. The analysis follows assumptions on the intensity distribution, the linear arrangement, and the regularity of point-like signatures. The proposed approach is validated using a high resolution staring spotlight TerraSAR-X image. A preliminary experiment for change detection using the extracted building features is also studied in this paper.","PeriodicalId":350698,"journal":{"name":"2015 IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSAR.2015.7306218","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The grammar of facade structures is often related to regularly distributed signature patterns in high-resolution synthetic aperture radar (SAR) images. Given the structural details in the SAR image, algorithms for building extraction/monitoring should exploit this contextual information for an object-based analysis. In this paper we propose a framework to extract detailed high rise building features including building masks, orientations and stories. We developed a top-down approach which consists of processing at three levels, namely image level, region-of-interest (ROI) level and storey level. The analysis follows assumptions on the intensity distribution, the linear arrangement, and the regularity of point-like signatures. The proposed approach is validated using a high resolution staring spotlight TerraSAR-X image. A preliminary experiment for change detection using the extracted building features is also studied in this paper.