• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.431-447
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• 2021

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.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.252-256
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• 1998

Accurate mapping of satellite images is one of the most important Parts in many remote sensing applications. Since the position and the attitude of a satellite during image acquisition cannot be determined accurately enough, it is normal to have several hundred meters' ground-mapping errors in the systematically corrected images. The users which require a pixel-level or a sub-pixel level mapping accuracy for high-resolution satellite images must use a number of Ground Control Points (GCPs). In this paper, the performance of two geometric correction algorithms is tested and compared. One is the polynomial warping algorithm which is simple and popular enough to be implemented in most of the commercial satellite image processing software. The other is full camera modelling algorithm using Physical orbit-sensor-Earth geometry which is used in satellite image data receiving, pre-processing and distribution stations. Several criteria were considered for the performance analysis : ultimate correction accuracy, GCP representatibility, number of GCPs required, convergence speed, sensitiveness to inaccurate GCPs, usefulness of the correction results. This paper focuses on the usefulness of the precision correction algorithm for regular image pre-processing operations. This means that not only final correction accuracy but also the number of GCPs and their spatial distribution required for an image correction are important factors. Both correction algorithms were implemented and will be used for the precision correction of KITSAT-3 images.

• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.1
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• pp.8-17
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• 1998

This paper presents a method of construction and re-use of a GCP database for precision geometric correction of high resolution satellite images. Accurate geometric correction can be achieved by using accurate GCPs. The GCP information which is extracted from maps or other sources is saved in a database in conjunction with the corresponding image chips. The usage of the GCPs from the database gives reusability and efficiency in marking new GCPs. An image matching algorithm was developed to determine the corresponding positions between an image chip and a new image. The proposed technique can save time in the regular operation of satellite image preprocessing by propagating the pre-determined GCPs to the new image correction.

• Korean Journal of Remote Sensing
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• v.14 no.2
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• pp.137-148
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• 1998

An algorithm developed for the precision correction of high resolution satellite images is introduced in this paper. In general, the polynomial warping algorithm which derives polynomial equations between GCPs extracted from an image and a base map requires many GCPs well-distributed over the image. The precision correction algorithm described in this paper is based on a sensor-orbit-Earth geometry, and therefore, it is capable of correcting a raw image using only 2-3 GCPs. This algorithm estimates the errors on the orbit determination and the attitude of the satellite by using a Kalman filter. This algorithm was implemented, tested and integrated into the KITSAT-3 image preprocessing software.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.151-156
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• 2002

A new position correction method using four fiducials as reference points was developed and examined. It was aimed to calibrate nonlinear deformation by numerous error sources. A correlation for correction was derived from the geometric relationship between four fiducials and chip position. Compared with three points method, it exhibited more accurate correction, especially for inner area of a quadrilateral composed of four fiducial points. Its accuracy was found to be increased as fiducials moves outwardly within a printed circuit board (PCB) and/or as they form more rectangle-like shape As for arbitrarily nonlinear deformation, this method can be applied using more than five fiducials. In this case, local-area calibration is carried out by sectioning a board area into several rectangular are as.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.4
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• pp.97-103
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• 2001

Accuracy of a machined part is determined by the relative motion between the cutting tool and the workpiece. One of the important factors which affects the relative motion is the geometric errors of a machine tool. In this study, firstly, geometric errors are measured by laser interferometer, and the positioning error of each control point selected uniformly on the control surface CAD model can be estimated from th oirm shaping model and geometric error data base. Where a form shaping function is derived from the link of homogeneous transformation matrix. Secondly, control points are shifted to the estimated amount of positioning errors. A new control surface is modeled with NURBS(Non Uniform Rational B-Spline) surface approximation to the shifted control points. By generating tool paths to the redesigned control surface, we reduce the machining error quite.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.429-431
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• 2010

The hybrid geoid model should be determined by fitting the gravimetric geoid to the geometric geoid which were presented the local vertical level. Therefore, it is necessary to find firstly the optimal scheme for improving the accuracy of gravimetric geoid in order to development the high-precision hybrid geoid model. Through finding the optimal scheme for determining the each part of gravimetric geoid, the most accurate gravimetric geoid model in Korea will be developed when the EIGEN-CG03C model to degree 360, 4-band spherical FFT and RTM reduction methods were used for determining the long, middle and short-frequency part of gravimetric geoid respectively. Finally, we developed the hybrid geoid model around Korea by correcting to gravimetric geoid with the correction term. The correction term is modelled using the difference between GPS/Levelling derived geoidal heights and gravimetric geoidal heights. The stochastic model used in the calculation of correction term is the LSC technique based on second-order Markov covariance function. 503 GPS/Levelling data were used to model the correction term. The degree of LSC fitting to the final hybrid geoid model in Korea was evaluated as 0.001m ${\pm}0.054m$.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.287-288
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• 2006

This paper introduces an approach of method to compensate accuracy error of diagonal direction. The measurement of squareness error is an important parameter in performance test of two axis Linear Motor and this exerts influence on accuracy error of diagonal test. However, previous knowledge management approaches are limited in deviation measurement of optical axis or restrictive elements of diagonal measurements using laser interferometer. But this proposed method calculated diagonal accuracy error which was occurred by squareness error and compensated squareness error using orthogonal correction method of PMAC. From this result, diagonal accuracy error is significantly reduced. This experimental results show that geometric error of squareness error is easily corrected by dynamic coordinate correction.

• 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.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.907-917
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• 2019

Recently, the demand for high-resolution satellite images increases in many fields such as land monitoring and terrain analysis. Therefore, the need for geometric correction is increasing. As an automatic precision geometric correction method, there is a method of automatically extracting the GCP by matching between the GCP Chip and the satellite image. For automatic precision geometric correction, the success rate of matching GCP Chip and satellite image is important. Therefore, it is important to evaluate the matching performance of the manufactured GCP Chip. In order to evaluate the matching performance of GCP Chips, a total of 3,812 GCP Chips in South Korea were used as experimental data. The GCP Chip matching results of KOMPSAT-3A and Google Map showed similar matching results. Therefore, we determined that Google Map satellite imagery could replace high-resolution satellite imagery. Also, presented a method using center point and error radius of Google Map to reduce the time required to verify matching performance. As a result, it is best to set the optimum error radius to 8.5m. Evaluated the matching performance of GCP Chips in South Korea using Google Maps. And verified matching result using presented method. As a result, the GCP Chip s in South Korea had a matching success rate of about 94%. Also, the main matching failure factors were analyzed by matching failure GCP Chips. As a result, Except for GCP Chips that need to be remanufactured, the remaining GCP Chips can be used for the automatic geometric correction of satellite images.