{"title":"结合顶帽、阈值和分水岭变换的三维逆合成孔径雷达图像分割","authors":"Asma Elyounsi, H. Tlijani, M. Bouhlel","doi":"10.1109/SETIT.2016.7939915","DOIUrl":null,"url":null,"abstract":"Segmentation is a critical step, preliminary to High-level processing such as classification, detection and object extraction from radar images. It provides an easier way to extract information in automatic target recognition (ATR) fields. However, extracting the shape of the target from this kind of images is very difficult task, so this paper presents a new approach for Radar image segmentation and how to be able to extract target shape from 3D Inverse Synthetic Aperture Radar (ISAR) Images by combining mathematical morphology watershed and thresholding methods with top-hat transformation.","PeriodicalId":426951,"journal":{"name":"2016 7th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Combining top-hat, thresholding and watershed transformation for 3D Inverse Synthetic Aperture Radar Images segmentation\",\"authors\":\"Asma Elyounsi, H. Tlijani, M. Bouhlel\",\"doi\":\"10.1109/SETIT.2016.7939915\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Segmentation is a critical step, preliminary to High-level processing such as classification, detection and object extraction from radar images. It provides an easier way to extract information in automatic target recognition (ATR) fields. However, extracting the shape of the target from this kind of images is very difficult task, so this paper presents a new approach for Radar image segmentation and how to be able to extract target shape from 3D Inverse Synthetic Aperture Radar (ISAR) Images by combining mathematical morphology watershed and thresholding methods with top-hat transformation.\",\"PeriodicalId\":426951,\"journal\":{\"name\":\"2016 7th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 7th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SETIT.2016.7939915\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 7th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SETIT.2016.7939915","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Combining top-hat, thresholding and watershed transformation for 3D Inverse Synthetic Aperture Radar Images segmentation
Segmentation is a critical step, preliminary to High-level processing such as classification, detection and object extraction from radar images. It provides an easier way to extract information in automatic target recognition (ATR) fields. However, extracting the shape of the target from this kind of images is very difficult task, so this paper presents a new approach for Radar image segmentation and how to be able to extract target shape from 3D Inverse Synthetic Aperture Radar (ISAR) Images by combining mathematical morphology watershed and thresholding methods with top-hat transformation.
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