• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.3-7
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• 1999

The images of the meteorological satellite NOAA contain geometrical distortions caused by its ambiguous position, its vibration, its sensor's movement, and so on. Geometric correction of satellite images is one of the most important parts in many remote sensing as the primary processing. Ground control points (GCP's) are necessary to check the accuracy of geometric correction and used for precise geometric correction. In this paper, a method for automatically selecting the residual error is presented. Calculating the effective angle and residual errors vector using the succeeded matching GCP's, precise geometric correction using an affine transformation is applied to systematically a corrected image. And the error is decreased by an affine transformation. The above enable the geometric correction of high quality.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.5 s.23
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• pp.67-74
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• 2002

The geometriccorrection of a satellite imagery is performed by making a systematic correction with satellite ephemerides and attitude angles followed by employing the Ground Control Points (GCSs) or Digital Elevation Models (DEMs). In a remote area or an inaccessible area, however, GCPs are unavailable to be surveyed and thus they can be obtained only by reading maps, which are not accurate in reality. In this study, we performed the systematic correction process to the inaccessible area and the precise geometric correction process to the adjacent accessible area by using GCPs. Then we analyzed the correlation between the two geo-referenced Korea Multiurpose Satellite (KOMPSAT-1 EOC) images. A new geometrical correction for the inaccessible area imagery is achieved by applying the correlation to the inaccessibleimagery. By employing this new method, the accuracy of the inaccessible area imagery is significantly improved absolutely and relatively.

• Korean Journal of Remote Sensing
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• v.15 no.4
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• pp.339-348
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• 1999

To extract value-added products which are important in scientific area and practical life, e.g. digital elevation models, ortho-rectified images and geometric corrected images, Satellite Technology Research Center at Korea Advanced Institute of Science and Technology has developed a satellite image processing software called "Valadd-Pro". In this paper, "Valadd-Pro" software is briefly introduced and its main components such as precise geometric correction, ortho-rectification and digital elevation model extraction component are described. The performance of "Valadd-Pro" software was assessed on 10m resolution 6000 $\times$ 6000 SPOT panchromatic images (60km $\times$ 60km) using ground control points from GPS measurements. The height accuracy was measured by comparing our results with 100m resolution $DTEDs^{1)}$ produced by USGS and 60m resolution DEMs generated from digitized contours produced by National Geography Institute. Also, to show the superior performance of "Valadd-Pro" software, we compared the performance with that of commonly used PCI$\circledR$ commercial software. Based on the results, the geometric correction of "Valadd-Pro" software needs fewer ground control points than that of PCI$\circledR$ software and the ortho-rectification of "Valadd-Pro" software shows similar performance to that of PCI$\circledR$ software. In the digital elevation model extraction, "Valadd-Pro" software is two times more accurate and four times faster than PCI$\circledR$ software.ccurate and four times faster than PCI$\circledR$ software.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.317-320
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• 2007

This research focuses on a network based data distribution and visualization system of Multi-functional Tran-port SATellite (MTSAT). Institute of Industrial Science (IIS) and Institute of Earthquake Research Institute (ERI) both at University of Tokyo have been receiving, processing, archiving and distributing of MTSAT imagery with a direct receiving of High Rate Information Transmit (HRIT) since October 2006. A software package, mtsatgeo, is developed including radiometric correction, geometric correction and spatial subset, and they are available on a web-based data distribution and processing service accessed at http://webgms.iis.u-tokyo.ac.jp/.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.2
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• pp.129-138
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• 2023

Acquiring precise coordinates of ground targets can be regarded as the key mission of the tactical-level military UAS(Unmanned Aerial System) operations. The coordinates deviations for the ground targets estimated from UAV (Unmanned Aerial Vehicle) images may depend on the sensor specifications and slant ranges between UAV and ground targets. It has an order of several tens to hundreds of meters for typical tactical UAV mission scenarios. In this paper, we propose a scheme that precisely acquires target coordinates from UAS by mapping image pixels to geographical coordinates based on GCP(Ground Control Points). This scheme was implemented and tested from ground control station for UAS. We took images of targets of which exact location is known and acquired the target coordinates using our proposed scheme. The experimental results showed that errors of the acquired coordinates remained within an order of several meters and the coordinates accuracy was significantly improved.

• Progress in Medical Physics
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• v.2 no.2
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• pp.183-192
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• 1991

Ophthalmoscopy following the intravenous injection of fluorescein has gained great diagnostic importance in ophthalmology. This technique provides sequential evaluation of the anatomic and physiologic status of the choroidal and retinal vasculature. In order to detect the changes between fluorescein ocular fundus image frames, the direct subtraction of the two frames is inadequate because of geometric distortions and background gray level differences in two images. In this study, a scheme for the correction of the geometric distortions is proposed. Precise control point coordinate values for transformation functions are manually determined after the process including a series of blood vessel detection and thinning, and one frame is mapped to another, and then a geometric distortion corrected image is obtained. When the corrected image is used in interframe change detections, a sucessful result is ensured.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1365-1367
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• 2003

A new method, called dynamic space projection method that is suitable to remote sensing image, is adopted to encrypt GCP (ground control point) datum in this paper. The essence of this method is to encrypt enough GCP by using a few known GCP in order to realize the precise correction of remote sensing image. By making use of the method to the GCP datum encrypting and precise geometric correction of TM image and SPOT image, the precision of encrypted GCP is less than one pixel, the precision of precisely corrected image is less than two pixels.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1058-1060
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• 2003

A ground control point (GCP) is a point on the surface of Earth where image coord inates and map coordinates can be identified. The GCP is useful for the geometric correction of systematic and unsystematic errors usually contained in a remotely sensed data. Especially in case of synthetic aperture radar (SAR) data, it has serious geometric distortions caused by inherent side looking geometry. In addition, SAR images are usually severely corrupted by speckle noises so that it is difficult to identify ground control points. We developed a ground point extraction algorithm that has an improved capability. An application of radargrammetry to Daejon area in Korea was studied to acquire the geometric information. For the ground control point extraction algorithm, an ERS SAR data with precise Delft orbit information and rough digital elevation model (DEM) were used. We analyze the accuracy of the results from our algorithm by using digital map and GPS survey data.

• Journal of Astronomy and Space Sciences
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• v.33 no.4
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• pp.313-318
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• 2016

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.103-114
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• 2024

The escalating demands for high-resolution satellite imagery necessitate the dissemination of geospatial data with superior accuracy.Achieving precise positioning is imperative for mitigating geometric distortions inherent in high-resolution satellite imagery. However, maintaining sub-pixel level accuracy poses significant challenges within the current technological landscape. This research introduces an approach wherein upsampling is employed on both the satellite image and ground control points (GCPs) chip, facilitating the establishment of a high-resolution satellite image precision sensor orientation. The ensuing analysis entails a comprehensive comparison of matching performance. To evaluate the proposed methodology, the Compact Advanced Satellite 500-1 (CAS500-1), boasting a resolution of 0.5 m, serves as the high-resolution satellite image. Correspondingly, GCP chips with resolutions of 0.25 m and 0.5 m are utilized for the South Korean and North Korean regions, respectively. Results from the experiment reveal that concurrent upsampling of satellite imagery and GCP chips enhances matching performance by up to 50% in comparison to the original resolution. Furthermore, the position error only improved with 2x upsampling. However,with 3x upsampling, the position error tended to increase. This study affirms that meticulous upsampling of high-resolution satellite imagery and GCP chips can yield sub-pixel-level positioning accuracy, thereby advancing the state-of-the-art in the field.