• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.652-655
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• 2004

The geometry of satellite image captured by linear pushbroom scanner is different from that of frame camera image. Since the exterior orientation parameters for satellite image will vary scan line by scan line, the epipolar geometry of satellite image differs from that of frame camera image. As we know, 2D affine orientation for the epipolar image of linear pushbroom scanners system are well-established by using the collinearity equation (Testsu Ono, 1999). Also, another epipolar geometry of linear pushbroom scanner system is recently established by Habib(2002). He reported that the epipolar geometry of linear push broom satellite image is realized by parallel projection based on 2D affine models. Here, in this paper, we compared the Ono's method with Habib's method. In addition, we proposed a method that generates epipolar resampled images. For the experiment, IKONOS stereo images were used in generating epipolar images.

• Korean Journal of Remote Sensing
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• v.18 no.2
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• pp.97-105
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• 2002

In this paper, we proposed a simplified strategy for the epipolarity of linear pushbroom imagery. The proposed strategy is verified on "Gupta and Hartly" sensor model and "Orun and Natarajan" sensor model. It is also compared with the precise epipolarity model of each sensor model on SPOT and KOMPSAT imagery. For the quantitative analysis, 20 ground control points are used as independent checking points. Based on the results, the accuracy of the proposed strategy is not different from that of the precise epipolarity model of each sensor model (below 0.1 pixels). Under the worst circumstance, the proposed strategy is robust. We can assure that the proposed strategy will show high accuracy on most of sensor models based on the co-linearity equations.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.182-187
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• 1999

Stereo matching is one of the most crucial parts in DEM generation. Naive stereo matching algorithms often create many holes and blunders in a DEM and therefore a carefully designed strategy must be employed to guide stereo matching algorithms to produce “good” 3D information. In this paper, we describe one such a strategy designed by the use of scene geometry, in particular, the epipolarity for generation of a DEM from linear pushbroom images. The epipolarity for perspective images is a well-known property, i.e., in a stereo image pair, a point in the reference image will map to a line in the search image uniquely defined by sensor models of the image pair. This concept has been utilized in stereo matching by applying epipolar resampling prior to matching. However, the epipolar matching for linear pushbroom images is rather complicated. It was found that the epipolarity can only be described by a Hyperbola- shaped curve and that epipolar resampling cannot be applied to linear pushbroom images. Instead, we have developed an algorithm of incorporating such epipolarity directly in least squares correlation matching. Experiments showed that this approach could improve the quality of a DEM.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1162-1164
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• 2003

The methods of the geometric reconstruction and sensor calibration of satellite linear pushbroom images are investigated. The model of the sensor used is based on the SPOT model that is developed by Kraiky. The satellite trajectory is a Keplerian trajectory in the approximation. Four orbit parameters, longitude of the ascending node(${\omega}$), inclination of the orbit plan(I), latitude argument of the satellite(W) and distance between earth center and satellite, are used for the camera modeling. Time-dependent orbit parameters are expressed by quadratic polynomials. SPOT-5 images have been used for validation tests. The results are that the RMSE acquired from 20 GCPs is 1.763m and the RMSE of 5 checking points 2.470m. Because the ground resolution of SPOT-5 is 2.5m, the result obtained in this study has a good accuracy. It demonstrates that the sensor model developed by this study can be used to reconstruct the geometry of satellite image using pushbroom camera.

• Korean Journal of Remote Sensing
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• v.13 no.2
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• pp.85-98
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• 1997

A geometric model of pushbroom-type linear CCD camera images is proposed in this paper. At present, this type of cameras are used for obtaining almost all kinds of high-resolution optical images from satellites. The proposed geometric model includes not only a forward transformation which is much more efficient. An inverse transformation function cannot be derived analytically in a closed form because the focal point of an image varies with time. In this paper, therefore, an iterative algorithm in which a focal point os converged to a given pixel position is proposed. Although the proposed model can be applied to any pushbroom-type linear CCD camera images, the geometric model of the high-resolution multi-spectral camera on-board KITSAT-3 is used in this paper as an example. The flight model of KITSAT-3 is in development currently and it is due to be launched late 1998.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.315-318
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• 2006

Pushbroom 방식의 CCD 영상에서 발생하는 pixel들 사이의 Non-uniformity 원인은 CCD pixel 면적의 차이, Dark current 영향, Output amplifier 차이, input radiance의 차이 등과 같은 CCD의 특성에 의해 발생하게 되며, CCD의 특성에 의해 발생되는 pixel사이의 상대복사량 차이인 Non-uniformity errors은 위성영상에서 줄무늬의 일차적 원인이 된다. 이러한 CCD의 상대복사보정을 위해서는 일차적으로 CCD의 특성을 잘 파악할 수 있는 지상에서 보정 값이 계산되어져야 하며 위성발사 후 보정 값이 다시 update 되어야 한다. 본 연구에서는 다목적실용위성2호의 상대복사보정을 위한 준비로서, 지상에서 만들어진 MSC CCD PAN1 영상과 Pushbroom 방식의 다목적실용위성1호 영상을 시험자료로 이용하여 pixel 사이의 줄무늬를 제거하기 위한 상대복사보정을 수행하였다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1165-1167
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• 2003

Geometric corrections are required to compensate skew effects, earth rotation effects and so on. Parameters for geometric modeling can be acquired from the metadata information. These parameters allow to locate on ground every pixel of acquired images. In this paper, we tested the precision of geometric modeling of linear pushbroom images, acquired by SPOT 3 and 5 using the satellite orbit information itself without additional external data. The result acquired from examination to recovery the geometry of image using 30 GCPs have about 650m RMSE in SPOT 3 and about 170m RMSE in SPOT 5.

• 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).

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.543-547
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• 2002

In this paper, we introduce a more improved camera modeling method for linear pushbroom images than the method proposed by Orun and Natarajan(ON). ON model shows an accuracy of within 1 pixel if more than 10 ground control points(GCPs) are provided. In general, there is high correlation between platform position and attitude parameters but ON model ignores attitude variation in order to overcome such correlation. We propose a new method that obtains an optimal solution set of parameters without ignoring the attitude variation. We first assume that attitude parameters are constant and estimate platform position's. Then we estimate platform attitude parameters using the values of estimated position parameters. As a result, we can set up an accurate camera model for a linear pushbroom satellite scene. In particular, we can apply the camera model to its surrounding scenes because our model provide sufficient information on satellite's position and attitude not only for a single scene but also for a whole imaging segment. We tested on two images: one with a pixel size 6.6m$\times$6.6m acquired from EOC(Electro Optical Camera), and the other with a pixel size 10m$\times$l0m acquired from SPOT. Our camera model procedures were applied to the images and gave satisfying results. We had obtained the root mean square errors of 0.5 pixel and 0.3 pixel with 25 GCPs and 23 GCPs, respectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1151-1156
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• 2013

In this study, to clearly establish the concept of a geometric modeling I apply for the concept of Pushbroom, limited to two-dimensional radiation Locator to provide a three-dimensional information purposes. Respect to the radiation scanner Pushbroom modeling techniques, geometric modeling method was presented introduced to extract three-dimensional information as long as the rotational component of the Gamma-Ray Linear Pushbroom Stereo System, introduced the two-dimensional and three-dimensional spatial information in the matching relation that can be induced. In addition, the pseudo-inverse matrix by using the conventional least-squares method, GCP(Ground Control Point) to demonstrate compliance by calculating the key parameters. Projection transformation matrix is calculated for obtaining three-dimensional information from two-dimensional information can be used as the primary relationship, and through the application of a radiation image matching technology will make it possible to extract three-dimensional information from two-dimensional X-ray imaging.