• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.750-752
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• 2003

The objective of this investigation is to compare the geometric precision of Rigorous Sensor Model and Rational Function Model for QuickBird images. In rigorous sensor model, we use the on-board data and ground control points to fit an orbit; then, a least squares filtering technique is applied to collocate the orbit. In rational function model, we first use the rational polynomial coefficients provided by the satellite company. Then the systematic bias of the coefficients is compensated by an affine transformation using ground control points. Experimental results indicate that, the RFM provides a good approximation in the position accuracy.

• 대한토목학회논문집
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• 제26권6D호
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• pp.1025-1032
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• 2006

고해상도 위성의 센서모형화는 도면화와 지형공간정보(Geo-spatial Information System)의 응용을 위해서는 필수적인 단계이다. 영상과 대상물과의 기하학적인 관계를 규정하는 센서모형은 크게 엄밀(rigorous)센서모형화와 간략(approximate)센서모형화의 두 가지로 나눌 수 있다. 엄밀센서모형화는 위성의 실제적인 촬영기하를 고려한 것으로 센서의 내외부적인 특성을 알고 있어야 하는 반면에 간략센서모형화 방법은 영상취득기하의 종합적인 이해나 센서의 내외부적인 특성정보를 필요로 하지 않기 때문에 사진측량 커뮤니티에서 많은 관심이 증대되고 있다. 본 연구에서는 고해상도 위성영상의 3차원 위치결정에 이용되고 있는 엄밀센서모형과 다양한 간략센서모형에 대해 비교연구를 수행하였으며 위성영상의 이용목적에 따른 적합한 모형화 방법을 제안하였다. IKONOS 위성영상을 이용한 사례연구를 통하여 엄밀센서모형과 간략센서모형에 대한 비교연구를 수행하였으며, 수집 가능한 지상기준점에 따른 위치정확도를 평가하였다. 간략센서모형화 방법 중에서 편의보정된 다항식비례모형(bias compensated RFM)이 가장 우수하였으며 개량평행투영모형(modified parallel projection)과 평행-중심투영모형(parallel-perspective model)은 적은 수의 기준점을 이용하여 센서모형화가 가능하였다. 또한 간략센서모형화 방법 중 부등각사상변환(affine transformation)은 고해상도 위성의 수평위치결정과 영상간의 등록에 활용가능하다.

• 대한공간정보학회지
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• 제12권2호
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• pp.67-71
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• 2004

위성영상의 종류가 증가하고 취득이 용이해 짐에 따라 위성영상을 이용한 수치고도모형의 생성에 관한 연구가 활발히 진행되어 왔다. SPOT의 경우 $60km{\times}60km$에 해당하는 광범위한 지역에 대한 영상을 취득할 수 있어 넓은 지역에 대한 수치고도모형을 생성 할 수 있는 이점이 있다. 기존의 엄밀센서모형(Rigorous Sensor Model)의 경우 위성의 천문력자료(Ephemeris Data)와 지상기준점을 사용하여 복잡한 과정을 거쳐 DEM을 생성하였으나 본 연구에서는 직접선형변환(DLT)에 기반을 둔 대안적 모형화 기법을 이용하여 DEM을 생성해 보았다. 결과적으로 직접선형 변환의 경우 소수의 기준점을 통하여 양호한 품질의 DEM을 취득할 수 있음을 확인 할 수 있었다.

• Korean Journal of Geomatics
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• 제4권1호
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• pp.31-37
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• 2004

The aim of this research is comparing the existing approximation models (e.g. Affine Transformation and Direct Linear Transformation) with Rational Function Model as a substitute of rigorous sensor model of linear array scanner, especially push-broom sensor. To do so, this research investigates the mathematical model of each approximation method. This is followed by the assessments of accuracy of transformation from object space to image space by using simulated data generated by collinearity equations which incorporate or depict the physical aspects of linear array sensor.

• 한국측량학회지
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• 제31권6_2호
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• pp.577-583
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• 2013

Recently, massive archives of ground information imagery from new sensors have become available. To establish a functional relationship between the image and the ground space, sensor models are required. The rational functional model (RFM), which is used as an alternative to the rigorous sensor model, is an attractive option owing to its generality and simplicity. To determine the rational polynomial coefficients (RPC) in RFM, however, we encounter the problem of obtaining a stable solution. The design matrix for solutions is usually ill-conditioned in the experiments. To solve this unstable solution problem, regularization techniques are generally used. In this paper, we describe the effective determination of the optimal regularization parameter in the regularization technique during RPC derivation. A brief mathematical background of RFM is presented, followed by numerical approaches for effective determination of the optimal regularization parameter using the Euler Method. Experiments are performed assuming that a tilted aerial image is taken with a known rigorous sensor. To show the effectiveness, calculation time and RMSE between L-curve method and proposed method is compared.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.225-227
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• 2003

Traditional photogrammetry and satellite image rectification technique have been developed based on control-points for many decades. These techniques are driven from linked points in image space and the corresponding points in the object space in rigorous colinearity or coplanarity conditions. Recently, digital imagery facilitates the opportunity to use features as well as points for images rectification. These implementations were mainly based on rigorous models that incorporated geometric constraints into the bundle adjustment and could not be applied to the new high-resolution satellite imagery (HRSI) due to the absence of sensor calibration and satellite orbit information. This research is an attempt to establish a new Line Based Transformation Model (LBTM), which is based on linear features only or linear features with a number of ground control points instead of the traditional models that only use Ground Control Points (GCPs) for satellite imagery rectification. The new model does not require any further information about the sensor model or satellite ephemeris data. Synthetic as well as real data have been demonestrated to check the validity and fidelity of the new approach and the results showed that the LBTM can be used efficiently for rectifying HRSI.

• Korean Journal of Geomatics
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• 제3권1호
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• pp.23-32
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• 2003

Rigorous sensor and dynamic modeling techniques are required if spatial information is to be accurately extracted from video imagery. First, a mathematical model for an uncalibrated video camera and a description of a bundle adjustment with added parameters, for purposes of general block triangulation, is presented. This is followed by the application of invariance-based techniques, with constraints, to derive initial approximations for the camera parameters. Finally, dynamic modeling using the Kalman Filter is discussed. The results of various experiments with real video imagery, which apply the developed techniques, are given.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.82-87
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• 2002

RFM is the sensor model of IKONOS imagery for end-users. IKONOS imagery vendors provide RPC (Rational Polynomial Coefficients), Ration Function Model coefficients for IKONOS, for end-users with imagery. So it is possible that end-users obtain geospatial information in their IKONOS imagery without additional any effort. But there are requirements still fur rigorous 3D positions on RPC user. Provided RPC can not satisfy user and company to generate precision 3D terrain model. In IKONOS imagery, physical sensor modeling is difficult because IKONOS vendors do not provide satellite ephemeris data and abstract sensor modeling requires many GCP well distributed in the whole image as well as other satellite imagery. Therefore RPC modification is better choice. If a few GCP are available, RPC can be modified by method which is introduced in this paper. Study on evaluation modified RPC in IKONOS reports reasonable result. Pseudo GCP generated with vendor's RPC and additional GCP make it possible through sequential solution.

• 항공우주기술
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• 제7권2호
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• pp.187-195
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• 2008

고해상도의 인공위성 데이터로부터 지상좌표를 해석하는 센서모델링 기술은 위성영상자료의 활용 확대 및 신뢰성 확보에 가장 중요한 연구부분으로서 이에 대한 연구과 증가되고 있다. 본 연구는 이러한 요구조건을 기본을 하여, 고해상도 인공위성에서 기본적으로 탑재되어 있는 GPS, Star-tracker, Gyro 등의 센서로부터 측정된 위성의 위치, 속도, 자세 및 시간 정보를 이용하여 위성자료로부터 지상좌표를 해석하는 direct sensor model (DSM)과 위성의 궤도 정보를 얻을 수 없는 경우나 궤도에 대한 정보가 불확실하여 물리적 센서모델로는 지형보정을 수행할 수 없는 경우에 사용될 수 있는 rational function model (RFM)의 적용하여 지상좌표를 해석하는 방법에 대해 살펴보고자 한다.

• 대한원격탐사학회지
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• 제25권3호
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• pp.205-214
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• 2009

This paper investigates stereo 3D viewing for linear pushbroom satellite images using the Orbit-Attitude Model proposed by Kim (2006) and using OpenGL graphic library in Digital Photogrammetry Workstation. 3D viewing is tested with KOMPSAT-2 satellite stereo images, a large number of GCPs (Ground control points) collected by GPS surveying and orbit-attitude sensor model as a rigorous sensor model. Comparison is carried out by two accuracy measurements: the accuracy of orbit-attitude modeling with bundle adjustment and accuracy analysis of errors in x and y parallaxes. This research result will help to understand the nature of 3D objects for high resolution satellite images, and we will be able to measure accurate 3D object space coordinates in virtual or real 3D environment.