{"title":"基于组合模板的SAR图像识别","authors":"Liu Kaiqi, Wang Wenguang, S. Zuowei","doi":"10.1109/IST.2013.6729707","DOIUrl":null,"url":null,"abstract":"In this paper, a new recognition algorithm of SAR image which is based on combined templates has been proposed. The new algorithm is based on the traditional mean templates recognition. We use some statistical information of the training samples to make a refusing threshold, which is expected to have the ability that can refuse the non-template-class targets effectively. Meanwhile, the proposed combined templates algorithm can re-recognize those refused targets by another target recognition method called recognition based on features of graphic image knowledge so that we can improve the final recognizing efficiency. Finally, we use MSTAR database to detect the target recognition ability, which can indicate that the algorithm we proposed is effective.","PeriodicalId":448698,"journal":{"name":"2013 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Recognition of SAR image based on combined templates\",\"authors\":\"Liu Kaiqi, Wang Wenguang, S. Zuowei\",\"doi\":\"10.1109/IST.2013.6729707\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new recognition algorithm of SAR image which is based on combined templates has been proposed. The new algorithm is based on the traditional mean templates recognition. We use some statistical information of the training samples to make a refusing threshold, which is expected to have the ability that can refuse the non-template-class targets effectively. Meanwhile, the proposed combined templates algorithm can re-recognize those refused targets by another target recognition method called recognition based on features of graphic image knowledge so that we can improve the final recognizing efficiency. Finally, we use MSTAR database to detect the target recognition ability, which can indicate that the algorithm we proposed is effective.\",\"PeriodicalId\":448698,\"journal\":{\"name\":\"2013 IEEE International Conference on Imaging Systems and Techniques (IST)\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Imaging Systems and Techniques (IST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IST.2013.6729707\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Imaging Systems and Techniques (IST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IST.2013.6729707","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognition of SAR image based on combined templates
In this paper, a new recognition algorithm of SAR image which is based on combined templates has been proposed. The new algorithm is based on the traditional mean templates recognition. We use some statistical information of the training samples to make a refusing threshold, which is expected to have the ability that can refuse the non-template-class targets effectively. Meanwhile, the proposed combined templates algorithm can re-recognize those refused targets by another target recognition method called recognition based on features of graphic image knowledge so that we can improve the final recognizing efficiency. Finally, we use MSTAR database to detect the target recognition ability, which can indicate that the algorithm we proposed is effective.