{"title":"基于GMM的视频sar运动目标检测方法","authors":"Meng Yan, L. Li, Haochuan Chen","doi":"10.1109/PRML52754.2021.9520711","DOIUrl":null,"url":null,"abstract":"In VideoSAR circle trace imaging mode, the energy of moving target is defocused and shifted. However, due to the occlusion of target height, there is shadow in its real position, which represents the lack of energy. In addition, there is a strong correlation between adjacent frames of VideoSAR image sequence, and the shadow also moves with the movement of the target. Based on this property, a new method for moving object detection in VideoSAR image sequences is proposed. This method is based on Gaussian mixture model. Firstly, it preprocesses the image sequence, uses sift + RANSAC algorithm and median filter processing, then uses Otsu threshold segmentation algorithm to transform the image into binary image, uses Gaussian mixture model to detect moving objects, and finally carries out morphological processing. Using VideoSAR image sequence of Sandia National Laboratory, the moving target can be detected effectively.","PeriodicalId":429603,"journal":{"name":"2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning (PRML)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A VideoSAR Moving Target Detection Method Based on GMM\",\"authors\":\"Meng Yan, L. Li, Haochuan Chen\",\"doi\":\"10.1109/PRML52754.2021.9520711\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In VideoSAR circle trace imaging mode, the energy of moving target is defocused and shifted. However, due to the occlusion of target height, there is shadow in its real position, which represents the lack of energy. In addition, there is a strong correlation between adjacent frames of VideoSAR image sequence, and the shadow also moves with the movement of the target. Based on this property, a new method for moving object detection in VideoSAR image sequences is proposed. This method is based on Gaussian mixture model. Firstly, it preprocesses the image sequence, uses sift + RANSAC algorithm and median filter processing, then uses Otsu threshold segmentation algorithm to transform the image into binary image, uses Gaussian mixture model to detect moving objects, and finally carries out morphological processing. Using VideoSAR image sequence of Sandia National Laboratory, the moving target can be detected effectively.\",\"PeriodicalId\":429603,\"journal\":{\"name\":\"2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning (PRML)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning (PRML)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PRML52754.2021.9520711\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning (PRML)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PRML52754.2021.9520711","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A VideoSAR Moving Target Detection Method Based on GMM
In VideoSAR circle trace imaging mode, the energy of moving target is defocused and shifted. However, due to the occlusion of target height, there is shadow in its real position, which represents the lack of energy. In addition, there is a strong correlation between adjacent frames of VideoSAR image sequence, and the shadow also moves with the movement of the target. Based on this property, a new method for moving object detection in VideoSAR image sequences is proposed. This method is based on Gaussian mixture model. Firstly, it preprocesses the image sequence, uses sift + RANSAC algorithm and median filter processing, then uses Otsu threshold segmentation algorithm to transform the image into binary image, uses Gaussian mixture model to detect moving objects, and finally carries out morphological processing. Using VideoSAR image sequence of Sandia National Laboratory, the moving target can be detected effectively.