W. Biamino, M. Borasi, M. Cavagnero, A. Croce, L. D. Matteo, F. Fontebasso, F. Tataranni, P. Trivero
{"title":"A “dynamic” land masking algorithm for synthetic aperture radar images","authors":"W. Biamino, M. Borasi, M. Cavagnero, A. Croce, L. D. Matteo, F. Fontebasso, F. Tataranni, P. Trivero","doi":"10.1109/IGARSS.2015.7326783","DOIUrl":null,"url":null,"abstract":"A novel approach to land masking in synthetic aperture radar (SAR) images is designed and implemented. The developed algorithm takes as input an archived shoreline from a public domain database and modifies it to draw the actual shoreline on SAR images by analysing backscatter values. Starting with data from the GSHHS (the global self-consistent hierarchical high-resolution shoreline database), coastline positioning is improved by evaluating the radiometric intensity gradient in coastal areas of the SAR image. A further enhancement is obtained by applying the Canny edge detection algorithm. The methodology is tested on Envisat and ERS images, as well as on ALOS and COSMO SkyMed images.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IGARSS.2015.7326783","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
A novel approach to land masking in synthetic aperture radar (SAR) images is designed and implemented. The developed algorithm takes as input an archived shoreline from a public domain database and modifies it to draw the actual shoreline on SAR images by analysing backscatter values. Starting with data from the GSHHS (the global self-consistent hierarchical high-resolution shoreline database), coastline positioning is improved by evaluating the radiometric intensity gradient in coastal areas of the SAR image. A further enhancement is obtained by applying the Canny edge detection algorithm. The methodology is tested on Envisat and ERS images, as well as on ALOS and COSMO SkyMed images.
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