• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.99-107
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• 2014

There are two types of Physical Model and RFM (Rational Function Model) is to determinate ground coordinates using KOMPSAT-2 and KOMPSAT-3 satellite data. Generally, RPCs(Rational Polynomial Coefficients) based on RFM is provided for users. This RPCs is to compute the ground coordinates to the image coordinates. If users produce ortho-image with provided RPCs is useful, directly compute the ground coordinates corresponding to image coordinates and check location accuracy etc. are difficult. In this study, a basic algorithm of inverse RPCs that calculates the image coordinates to ground coordinates, compute based on provided RPCs and evaluation of determinated ground coordinates using developed inverse RPCs were proposed.

• Aerospace Engineering and Technology
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• v.7 no.2
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• pp.187-195
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• 2008

Generation of accurate ground coordinates from high resolution satellite image are becoming increasingly of interest. The primary focus of this paper is to compute satellite direct sensor model (DSM) and rational function model (RFM) for accurate generation of ground coordinates from high resolution satellite images. Being based on this we presented an algorithm to be able to efficiently ground coordinates about large area with introducing RFM(rational function model) method applied to rigorous sensor modeling standing on basis of satellite orbit dynamics and collinearity equation, and sensor modeling of high-resolution satellite data like IKONOS, QuickBird, KOMPSAT-2 and others. The general high resolution satellite measures the position, velocity and attitude data of satellite using star, gyro, and GPS sensors.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.387-389
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• 2003

Rational function model (RFM) is a universal sensor model for remote sensing image restitution. It is able to substitute for models of all known sensors. In this paper, RFM generation by CCD linear image models is described in detail. A principle of RFM-based 3D reconstruction and its implementation in JX4 DPW is also described. Experiments using IKONOS and SPOT5 images are carried out on JX4 DPW. Results show that RFM generated is feasible for photogrammetric restitution of CCD linear images.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1D
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• pp.89-94
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• 2012

The RFM (Rational Function Model), as an alternative to physical sensor models has been widely used for photogrammetric processing of high resolution optical satellite imagery. However, the application of RF modeling to the SAR (Synthetic Aperture Radar) is very limited. In this paper, stereo radargrammetric processing of TerraSAR-X stereo pairs with RFM is implemented and analyzed. The investigation has shown that the accuracy of TerraSAR-X DSM is similar to that of the commercial S/W product. Finally, it is demonstrated that RFM is effective and feasible in the application to the radargrammetric SAR image processing.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.565-578
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• 2018

In this paper, we investigate the feasibility of modelling image strips, instead of individual scenes, that have been acquired from the same orbital pass through the process of bundle adjustments. Under this approach, First, a rational function model (RFM) of the strip image is generated from the RFMs of individual images, such that the entire strip of images can be treated as a single image. Correction parameters are calculated through bundle adjustments between strip images. For the experiment, we used two stereo strips. Each strip image consists of three KOMPSAT-3A scenes. Experimental results show that it was possible to improve the initial model by using the control points located in a specific region of the strip. We showed that absolute orientation with moderate accuracy of 2 m errors were achieved from 12 ground control points for the three-image strips. The test results indicate that bundle adjustment of strip images could be more efficient than bundle adjustments of the individual scenes.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1143-1145
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• 2003

Some of satellites such as IKONOS don't provide the orbital elements so that we can’ utilize the physical sensor model. Therefore, Rational Function Model(RFM) which is one of mathematical models could be a feasible solution. In order to improve 3D geopositioning accuracy of IKONOS stereo imagery, Rational Polynomial Coefficients(RPCs) of the RFM need to be updated with Ground Control Points(GCPs). In this paper, a method to improve RPCs of RFM using GCPs and 3D cube is proposed. Firstly, the image coordinates of GCPs are observed. And then, using offset values and scale values of RPC provided, the image coordinates and ground coordinates of 3D cube are initially determined and updated RPCs are computed by the iterative least square method. The proposed method was implemented and analyzed in several cases: different numbers of 3D cube layers and GCPs. The experimental results showed that the proposed method improved the accuracy of RPCs in great amount.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.518-523
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• 2002

Nowadays the Rational Function Model (RFM), an abstract sensor model, is substituting physical sensor models for highly complicated imaging geometry. But RFM is algorithm to be required many Ground Control Points (GCP). In case of RFM of the third order, At least forty GCP are required far RFM generation. The purpose of this study is to research more efficient algorithm on GCP and accurate algorithm similar to RFM. The Polynomial Camera Model is relatively accurate and requires a little GCP in comparisons of RFM. This paper introduces how to generate Polynomial Camera Model and fundamental algorithms for construction of 3-D topographic data using the Polynomial Camera Model information in the Kompsat stereo pair and describes how to generate the 3-D ground coordinates by manual matching. Finally we tried to extract height information for the whole image area with the stereo matching technique based on the correlation.

• Proceedings of the KSRS Conference
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• 2003.11a
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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.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.417-422
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• 2003

The KOMPSAT-2 MSC(Multi-Spectral Camera), with high spatial resolution, is currently under development and will be launched in the end of 2004. A sensor model relates a 3-D ground position to the corresponding 2-D image position and describes the imaging geometry that is necessary to reconstruct the physical imaging process. The Rational Function Model (RFM) has been considered as a generic sensor model. form. The RFM is technically applicable to all types of sensors such as frame, pushbroom, whiskbroom and SAR etc. With the increasing availability of the new generation imaging sensors, accurate and fast rectification of digital imagery using a generic sensor model becomes of great interest to the user community. This paper describes the procedure to generation of the RPC (Rational Polynomial Coefficients) for KOMPSAT-2 MSC.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.337-344
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• 2002

In general, in order to obtain position information from satellite images, satellite sensor model which represents the geometric relationship between sensor and targeted area should be established in the first place. However, it is not simple for modelling pushbroom satellite sensor due to the image capturing process. In recent development of new generation imaging sensors, a generic sensor model, which is applicable to all types of sensors such as frame, pushbroom, whiskbroom, and SAR is in great need to the remote sensing and photogrammetry community. In this paper, the RFM as sensor model was implemented with KOMPSAT EOC and SPOT satellite images and analyzed in cases where the number and distribution of ground control points were varied. The test results of RFM were presented and compared with those of Direct Linear Transformation(DLT).