{"title":"基于珞珈 3-02 卫星 VLR 模型的目标驱动型实时几何处理","authors":"Rongfan Dai;Mi Wang;Ru Chen;Zhiqi Zhang","doi":"10.1109/LGRS.2024.3452793","DOIUrl":null,"url":null,"abstract":"The on-board processing systems of high-resolution optical satellites performing hotspot observations must be of high efficiency and high precision. To meet these requirements, a real-time geometric correction (RGC) method was developed based on a target-driven virtual linear-array reimaging (VLR) model. First, the undistorted VLR was used instead of the original distorted physical linear array to achieve a relative orientation of the sub-images of the sensor, ensuring the relative geometric accuracy of the original multilinear array and multiband images. Next, the coordinate position of the region of interest (ROI) in the original image was accurately located in a step-by-step strategy. According to the object-space projection model (OPM) of the VLR and the physical strict model (PSM) of the original image, a coordinate mapping relationship could be established. Finally, the RGC of the ROI image was achieved through GPU-accelerated grayscale resampling. The method was then tested using panchromatic (PAN) and multispectral scanner (MSS) data of LuoJia3-02. The results showed that the processed images exhibited satisfactory band registration accuracy and maintained geometric consistency among various linear-array scanners. Furthermore, in terms of performance, the ROI processing speed was fully adapted to the imaging rate, which fulfilled the real-time on-board processing demands.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"21 ","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Target-Driven Real-Time Geometric Processing Based on VLR Model for LuoJia3-02 Satellite\",\"authors\":\"Rongfan Dai;Mi Wang;Ru Chen;Zhiqi Zhang\",\"doi\":\"10.1109/LGRS.2024.3452793\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The on-board processing systems of high-resolution optical satellites performing hotspot observations must be of high efficiency and high precision. To meet these requirements, a real-time geometric correction (RGC) method was developed based on a target-driven virtual linear-array reimaging (VLR) model. First, the undistorted VLR was used instead of the original distorted physical linear array to achieve a relative orientation of the sub-images of the sensor, ensuring the relative geometric accuracy of the original multilinear array and multiband images. Next, the coordinate position of the region of interest (ROI) in the original image was accurately located in a step-by-step strategy. According to the object-space projection model (OPM) of the VLR and the physical strict model (PSM) of the original image, a coordinate mapping relationship could be established. Finally, the RGC of the ROI image was achieved through GPU-accelerated grayscale resampling. The method was then tested using panchromatic (PAN) and multispectral scanner (MSS) data of LuoJia3-02. The results showed that the processed images exhibited satisfactory band registration accuracy and maintained geometric consistency among various linear-array scanners. Furthermore, in terms of performance, the ROI processing speed was fully adapted to the imaging rate, which fulfilled the real-time on-board processing demands.\",\"PeriodicalId\":91017,\"journal\":{\"name\":\"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society\",\"volume\":\"21 \",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10669995/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10669995/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Target-Driven Real-Time Geometric Processing Based on VLR Model for LuoJia3-02 Satellite
The on-board processing systems of high-resolution optical satellites performing hotspot observations must be of high efficiency and high precision. To meet these requirements, a real-time geometric correction (RGC) method was developed based on a target-driven virtual linear-array reimaging (VLR) model. First, the undistorted VLR was used instead of the original distorted physical linear array to achieve a relative orientation of the sub-images of the sensor, ensuring the relative geometric accuracy of the original multilinear array and multiband images. Next, the coordinate position of the region of interest (ROI) in the original image was accurately located in a step-by-step strategy. According to the object-space projection model (OPM) of the VLR and the physical strict model (PSM) of the original image, a coordinate mapping relationship could be established. Finally, the RGC of the ROI image was achieved through GPU-accelerated grayscale resampling. The method was then tested using panchromatic (PAN) and multispectral scanner (MSS) data of LuoJia3-02. The results showed that the processed images exhibited satisfactory band registration accuracy and maintained geometric consistency among various linear-array scanners. Furthermore, in terms of performance, the ROI processing speed was fully adapted to the imaging rate, which fulfilled the real-time on-board processing demands.