• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.69-82
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• 1998

SAR imagery can overcome the limitations of electro-optical sensor imagery and provide us Information which plays a supplementary role. But it is necessary to remove a variety of geometric errors in SAR imagery. An accurate geometric correction of SAR imagery is not easy task to achieve, though some techniques and theories are introduced. We also have difficulties such as transformation problem between 'International' ellipsoid in Radarsat system and 'Bessel' ellipsoid. Two widely used correction method, one is made by simulated image, and the other by collinearity equation, usually use DEM. In this study, the merits and demerits of geocoding methods respectively and the effective method for Korean terrain were found.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.339-342
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• 2002

동화상 압축에서 사용되는 움직임 벡터는 영상을 일정한 크기의 블록으로 나누어 이전 영상과 가장 예측 오류가 적은 곳을 지정하여 예측한다. 블록의 이동 정도는 수직. 수평의 선형적인 움직임(translational displacements)을 가정하여 사용하기 때문에 실제 화상에서 자주 나타나는 물체의 확대 또는 축소에 의한 크기 변화. 회전. 일그러짐 등의 변화에 올바르게 예측하지 못하는 문제를 가지고 있다. 본 논문은 블록의 선형적인 이동은 물론이고 4개 노드를 자유롭게 움직임일 수 있는 왜곡된 블록 정합 방식의 움직임 예측 기법에 대하여 소개하고 왜곡 블록 정합 방식에서 나타날 수 있는 기하학적인 오류를 수정하는 보정 방법에 관해 논의한다.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.15-23
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• 2004

In order to utilize remote sensed images effectively, it is necessary to correct geometric distortion. Geometric correction is a critical step to remove geometric distortions in satellite images. For geometric correction, Ground Control Points (GCPs) have to be chosen carefully to guarantee the quality of geocoded satellite images, digital maps, GPS surveying or other data. Traditional approach to geometric correction used GCPs requires substantial human operations. Also that is necessary much time and manpower. In this paper, we presented an on-line automatic geometric correction by constructing GCP Chip database. The Proposed on-line automatic geometric correction system is consists of four part. Input image, control the GCP Chip, revision of selected GCP, and output setting part. In conclusion, developed system reduced the processing time and energy for tedious manual geometric correction and promoted usage of Landsat imagery.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.18-24
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• 2004

SPECT technology is used for the reconstructed image in the field of industry noncontact measurement system. One of the distortion problems in reconstructed image quality is a collimator characterictic. The image distortion is caused by a geometrical structure of the collimator. This paper indicated a correction method to remove the image distortion by the structure of the collimator, and compared with the existing correction method. The correction. method removed the image distortion to use deconvolution of projection data with the shift-variant blurring function in the frequency domain. In this pater, I simulated with the collimator angle and distance between the detector and the center of object. and verified with expeimental data. The validity and limitation of correction method is studied for actual industrial applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3C
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• pp.264-270
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• 2010

Non-planar screens such as cylinder and sphere shaped screens are widely used for high-resolution immersive visualization environments. An existing method employs quadric matrix that maps an image onto a curved screen. However if the shape of the screen changes or moves, the quadric matrix will not be valid. In this paper, we assume that the screen is a quadric shape and the screen movement or change are relatively small. Then we propose to use a piecewise planar approximations for the screen to compensate for the geometric distortion on a non-planar screen. We demonstrate the effectiveness and efficiency of the proposed method through experiments.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.143-150
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• 2005

Camera image is very sensitive to illumination that result in difficulties for recognizing character. Also Camera captured document images have not only skew but also vignetting effect and geometric distortion. Vignetting effect make it difficult to separate characters from the document images. Geometric distortion, occurred by the mismatch of angle and center position between the document image and the camera, make the shape of characters to be distorted, so that the character recognition is more difficult than the case of using scanner. In this paper, we propose a method that can increase the performance of character recognition by correcting the geometric distortion of document images using a linear approximation which changes the quadrilateral region to the rectangle one. The proposed method also determine the quadrilateral transform region automatically, using the alignment of character lines and the skewed angles of characters located in the edges of each character line. Proposed method, therefore, can correct the geometric distortion without getting positional information from camera.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.49-57
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• 2012

An image reconstruction algorithm is proposed to estimate transmitted original images from images displayed on a video terminal. The proposed algorithm acquires images that are displayed on video terminal screens by using a camera. The transmitted images are then estimated with the acquired images. However, camera-acquired images exhibit geometric and color distortions caused by characteristics of the camera and display devices. We make use of a geometric distortion correction algorithm that exploits homography and color distortions using a weighted-linear model. The experimental results show that the proposed algorithm yields promising estimation performance with respect to the peak signal-to-noise ratio (PSNR). PSNR values of the estimated images with respect to the corresponding original images range from 28-29 dB.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.177-182
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• 2015

General method for correcting the distortion caused by the characteristic of the fish-eye lens may be classified in two ways. The first method is a calibration method using a mathematical model taking into account the characteristics of the lens, the second method is a method using only the distortion correction image, regardless of the lens. When considering the characteristics of the lens, calibration equation can be calculated geometrically from the relationship between the three-dimensional real-world coordinates and two-dimensional image coordinates and the parameters of lens. However, it is not suitable for ellipsoid type lens, because of existing research papers have been corrected on the spherical-type fisheye lens. In this paper, we propose a method for correcting geometrically using fish-eye lens as an ellipsoid model. Through a calibration picture, it can be seen that the proposed method is valid.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.3
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• pp.257-264
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• 1999

The lens distortions were corrected directly using the high-order polynomial which was offered in camera calibration data for the forward transformation and the root of Newton-Raphson's $2\times{2}$ nonlinear system for the backward transformation. The 0.04~0.08 pixels increase in accuracy was indicated through the use of direct correction of lens distortions instead of least square methods of commercial software. The least square adjustment method of high-order polynomial requires many control points which has a same weight. But this suggested method which is unnecessary to determine control points was developed and applied. The algorithm showed improved efficacy.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.270-274
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• 2009

한반도의 정밀관측을 목적으로 개발된 KOMPSAT-2위성의 영상을 활용하기 위해서는 촬영 시 발생하는 기하학적 왜곡의 보정이 필요하다. 본 연구에서는 지상기준점(Ground Control Point: GCP) 선택의 세 가지 특성을 각각 적용하여 기하보정을 하였다. 보정 영상의 정확도 검정을 위하여 수치지도(digital map)를 이용한 평균제곱근오차(Root Mean Square Error: RMSE)와 육안검사를 통해 정확도를 비교하였다. 그 결과 영상의 중앙은 선형 교차점을 선택한 방법이 가장 정확하였고, 가장자리는 건물의 모서리 또는 건물의 중심을 선택한 방법이 우수하였다.