{"title":"侧扫声纳图像的几何校正","authors":"Tal Sheffer, H. Guterman","doi":"10.1109/ICSEE.2018.8646188","DOIUrl":null,"url":null,"abstract":"The underwater environment makes object-detection missions difficult. Side-scan Sonar (SSS) has been found to be suitable for seabed scanning missions, however the sonar images acquired from SSS often suffer from considerable noise and geometrical distortion, which changes the understanding of the texture, size, and shape of seabed objects. In order to identify seabed objects, it is thus vital to reconstruct the actual shape by reducing distortion. This paper proposes a process for correcting and reconstructing the sonar image map that utilizes intensity normalization, slant range correction, yaw and pitch correction, and speed and location correction. This is done using navigation and inertial data acquired by the autonomous underwater vehicle sensors.","PeriodicalId":254455,"journal":{"name":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","volume":"578 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Geometrical Correction of Side-scan Sonar Images\",\"authors\":\"Tal Sheffer, H. Guterman\",\"doi\":\"10.1109/ICSEE.2018.8646188\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The underwater environment makes object-detection missions difficult. Side-scan Sonar (SSS) has been found to be suitable for seabed scanning missions, however the sonar images acquired from SSS often suffer from considerable noise and geometrical distortion, which changes the understanding of the texture, size, and shape of seabed objects. In order to identify seabed objects, it is thus vital to reconstruct the actual shape by reducing distortion. This paper proposes a process for correcting and reconstructing the sonar image map that utilizes intensity normalization, slant range correction, yaw and pitch correction, and speed and location correction. This is done using navigation and inertial data acquired by the autonomous underwater vehicle sensors.\",\"PeriodicalId\":254455,\"journal\":{\"name\":\"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)\",\"volume\":\"578 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSEE.2018.8646188\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSEE.2018.8646188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The underwater environment makes object-detection missions difficult. Side-scan Sonar (SSS) has been found to be suitable for seabed scanning missions, however the sonar images acquired from SSS often suffer from considerable noise and geometrical distortion, which changes the understanding of the texture, size, and shape of seabed objects. In order to identify seabed objects, it is thus vital to reconstruct the actual shape by reducing distortion. This paper proposes a process for correcting and reconstructing the sonar image map that utilizes intensity normalization, slant range correction, yaw and pitch correction, and speed and location correction. This is done using navigation and inertial data acquired by the autonomous underwater vehicle sensors.