Korean J. Remote Sens. 2021; 37(3): 431-447
Published online: June 30, 2021
https://doi.org/10.7780/kjrs.2021.37.3.6
© Korean Society of Remote Sensing
손종환 1)· 윤완상 1)· 김태정2),3)· 이수암 4)†
1) (주)쓰리디랩스 영상공학연구소 연구원 (Researcher, Image Engineering Research Center, 3DLabs Co., Ltd.) 2) 인하대학교 공간정보공학전공 정교수 (Professor, Department of Geoinformatic Engineering, Inha University) 3) 인하대학교 스마트시티공학전공 정교수 (Professor, Department of Geoinformatic Engineering, Inha University) 4) (주)쓰리디랩스 영상공학연구소 연구소장 (Director, Image Engineering Research Center, 3DLabs Co., Ltd.)
Recently, the use of high-resolution satellites is increasing in many areas. In order to supply useful satellite images stably, it is necessary to establish automatic precision geometric correction technic. Geometric correction is the process that corrected geometric errors of satellite imagery based on the GCP (Ground Control Point), which is correspondence point between accurate ground coordinates and image coordinates. Therefore, in the automatic geometric correction process, it is the key to acquire high-quality GCPs automatically. In this paper, we proposed iterative precision geometry correction method. we constructed an image pyramid and repeatedly performed GCP chip matching, outlier detection, and precision sensor modeling in each layer of the image pyramid. Through this method, we were able to acquire high-quality GCPs automatically. we then improved the performance of geometric correction of high-resolution satellite images. To analyze the performance of the proposed method, we used KOMPSAT-3 and 3A Level 1R 8 scenes. As a result of the experiment, the proposed method showed the geometric correction accuracy of 1.5 pixels on average and a maximum of 2 pixels.
Keywords High-resolution satellite image, Geometric correction, GCP matching, RANSAC, KOMPSAT-3, KOMPSAT-3A, CAS500
Korean J. Remote Sens. 2021; 37(3): 431-447
Published online June 30, 2021 https://doi.org/10.7780/kjrs.2021.37.3.6
Copyright © Korean Society of Remote Sensing.
손종환 1)· 윤완상 1)· 김태정2),3)· 이수암 4)†
1) (주)쓰리디랩스 영상공학연구소 연구원 (Researcher, Image Engineering Research Center, 3DLabs Co., Ltd.) 2) 인하대학교 공간정보공학전공 정교수 (Professor, Department of Geoinformatic Engineering, Inha University) 3) 인하대학교 스마트시티공학전공 정교수 (Professor, Department of Geoinformatic Engineering, Inha University) 4) (주)쓰리디랩스 영상공학연구소 연구소장 (Director, Image Engineering Research Center, 3DLabs Co., Ltd.)
Jong-Hwan Son 1)· Wansang Yoon 1)· Taejung Kim 2),3)· Sooahm Rhee 4)†
Recently, the use of high-resolution satellites is increasing in many areas. In order to supply useful satellite images stably, it is necessary to establish automatic precision geometric correction technic. Geometric correction is the process that corrected geometric errors of satellite imagery based on the GCP (Ground Control Point), which is correspondence point between accurate ground coordinates and image coordinates. Therefore, in the automatic geometric correction process, it is the key to acquire high-quality GCPs automatically. In this paper, we proposed iterative precision geometry correction method. we constructed an image pyramid and repeatedly performed GCP chip matching, outlier detection, and precision sensor modeling in each layer of the image pyramid. Through this method, we were able to acquire high-quality GCPs automatically. we then improved the performance of geometric correction of high-resolution satellite images. To analyze the performance of the proposed method, we used KOMPSAT-3 and 3A Level 1R 8 scenes. As a result of the experiment, the proposed method showed the geometric correction accuracy of 1.5 pixels on average and a maximum of 2 pixels.
Keywords: High-resolution satellite image, Geometric correction, GCP matching, RANSAC, KOMPSAT-3, KOMPSAT-3A, CAS500
Hyeon-Gyeong Choi, Sung-Joo Yoon, Sunghyeon Kim, Taejung Kim
Korean J. Remote Sens. 2024; 40(1): 103-114