• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.50.1-50.1
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• 2019

In coronagraph images, it is often observed that two successive CMEs merge into one another and form complex structures. This phenomenon, so called CME cannibalism caused by the differences in ejecting times and propagating velocities, can significantly degrade forecast capability of space weather, especially if it occur near the Earth. Regarding this, we attempt to analyze the cases that two CMEs are expecting to meet around 1 AU based on their arrival times. For this, we select 13 CME-CME pairs detected by ACE, Wind and/or STEREO-A/B. We find that 8 CME-CME pairs show a shock structure, which means they already met and became one structure. Meanwhile 5 pairs clearly show magnetic holes between two respective shock structures. Based on detailed investigation for each pair and statistical analysis for all events, we can get clues for following questions: 1) How does the solar wind structure change when they are merging? 2) Are there any systematic characteristics of merging process according to the CME properties? 3) Is the merging process associated with the occurrence of energetic storm particles? 4) What causes errors in calculating CME arrival times? Our results and discussions can be helpful to understand energetic phenomena not only close to the Sun but also near the Earth.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.83-91
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• 2004

An epipolar rectification is the process of transforming the epipolar geometry of a pair of images into a canonical form. This is accomplished by applying a homography to each image that maps the epipole to a predetermined point. In this process, rectified images transformed by homographies must be satisfied with the epipolar constraint. These homographies are not unique, however, we find out homographies that are suited to system's purpose by means of an additive constraint. Since the rectified image pair be a stereo image pair, we are able to find the disparity efficiently. Therefore, we are able to estimate the three-dimensional information of objects within an image and apply this information to object segmentation. This paper proposes a rectification method for object segmentation and applies the rectification result to the object segmentation. Using color and relative continuity of disparity for the object segmentation, the drawbacks of previous segmentation method, which are that the object is segmented to several region because of having different color information or another object is merged into one because of having similar color information, are complemented. Experimental result shows that the disparity of result image of proposed rectification method have continuity about unique object. Therefore we have confirmed that our rectification method is suitable to the object segmentation.

• Journal of IKEEE
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• v.17 no.1
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• pp.1-9
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• 2013

The quantitative evaluation of DEM(Digital Elevation Map) is very important to the assessment of the effectiveness for the applied 3D image analysis technique. This paper presents a new quantitative evaluation method of 3D reconstruction process by using synthetic images. The proposed method is based on the assumption that a preacquired DEM and ortho-image should be the pseudo ground truth. The proposed evaluation process begins by generating a pair of photo-realistic synthetic images of the terrain from any viewpoint in terms of application of the constructed ray tracing algorithm to the pseudo ground truth. By comparing the DEM obtained by a pair of photo-realistic synthetic images with the assumed pseudo ground truth, we can analyze the quantitative error in DEM and evaluate the effectiveness of the applied 3D analysis method. To verify the effectiveness of the proposed evaluation method, we carry out the quantitative and the qualitative experiments. For the quantitative experiment, we prove the accuracy of the photo-realistic synthetic image. Also, the proposed evaluation method is experimented on the 3D reconstruction with regards to the change of the matching window. Based on the fact that the experimental result agrees with the anticipation, we can qualitatively manifest the effectiveness of the proposed evaluation method.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.941-951
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• 2018

Utilization and demand of UAV (unmanned aerial vehicle) for the generation of 3D city model are increasing. In this study, we performed an experiment to adjustment position/orientation of UAV with incomplete attitude information and to extract point cloud data. In order to correct the attitude of the UAV, the rotation angle was calculated by using the continuous position information of UAV movements. Based on this, the corrected position/orientation information was obtained by applying IBA (Incremental Bundle Adjustment) based on photogrammetry. Each pair was transformed into an epipolar image, and the MDR (Multi-Dimensional Relaxation) technique was applied to obtain high precision DSM. Each extracted pair is aggregated and output in the form of a single point cloud or DSM. Using the DJI inspire1 and Phantom4 images, we can confirm that the point cloud can be extracted which expresses the railing of the building clearly. In the future, research will be conducted on improving the matching performance and establishing sensor models of oblique images. After that, we will continue the image processing technology for the generation of the 3D city model through the study of the extraction of 3D cloud It should be developed.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.337-343
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• 2004

Spatial information could be obtained from spaceborne high resolution optical and synthetic aperture radar(SAR) images. However, some satellite images do not provide physical sensor information instead, rational polynomial coefficients(RPC) are available. The objectives of this study are: (1) 3-dimensional ground coordinates were computed by applying rational function model(RFM) with the RPC for the stereo pair of Ikonos images and their accuracy was evaluated. (2) Interferometric SAR(InSAR) was applied to JERS-1 images to generate DEM and its accuracy was analysis. (3) Quality of the DEM generated automatically also analyzed for different types of terrain in the study site. The overall accuracy was evaluated by comparing with GPS surveying data. The height offset in the RPC was corrected by estimating bias. In consequence, the accuracy was improved. Accuracy of the DEMs generated from InSAR with different selection of GCP was analyzed. In case of the Ikonos images, the results show that the overall RMSE was 0.23327", 0.l1625" and 13.70m in latitude, longitude and height, respectively. The height accuracy was improved after correcting the height offset in the RPC. i.e., RMSE of the height was 1.02m. As for the SAR image, RMSE of the height was 10.50m with optimal selection of GCP. For the different terrain types, the RMSE of the height for urban, forest and flat area was 23.65m, 8.54m, 0.99m, respectively for Ikonos image while the corresponding RMSE was 13.82m, 18.34m, 10.88m, respectively lot SAR image.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.69-77
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• 2017

S The need for an automated geo-positioning approach for near real-time results and to boost cost-effectiveness has become increasingly urgent. Following this trend, a new approach to automatically compensate for the bias of the rational function model (RFM) was proposed. The core idea of this approach is to remove the bias of RFM only using tie points, which are corrected by matching with the digital elevation model (DEM) without any additional ground control points (GCPs). However, there has to be a additional evaluation according to the quality of DEM because DEM is used as a core element in this approach. To address this issue, this paper compared the quality effects of DEM in the conduct of the this approach using the Shuttle Radar Topographic Mission (SRTM) DEM with the spatial resolution of 90m. and the National Geographic Information Institute (NGII) DEM with the spatial resolution of 5m. One KOMPSAT-2 stereo-pair image acquired at Busan, Korea was used as experimental data. The accuracy was compared to 29 check points acquired by GPS surveying. After bias-compensation using the two DEMs, the Root Mean Square (RMS) errors were less than 6 m in all coordinate components. When SRTM DEM was used, the RMSE vector was about 11.2m. On the other hand, when NGII DEM was used, the RMSE vector was about 7.8 m. The experimental results showed that automated geo-positioning approach can be accomplished more effectively by using NGII DEM with higher resolution than SRTM DEM.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.583-590
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• 2012

This study proposes fusion image matching method according to land cover property to generate a detailed DEM using the high resolution IKONOS-2 stereo pair. A classified image, consists of building, crop-land, forest, road and shadow-water, is produced by color image with four bands. Edges and points are also extracted from panchromatic image. Matching is performed by the cross-correlation computing after five classes are automatically selected in a reference image. In each of building class, crop-land class, forest class and road class, matching was performed by the grid and edge, only grid, only grid, grid and point, respectively. Shadow-water class was excepted in the matching because this area causes excessive error of the DEM. As the results, edge line, building and residential area could be expressed more dense than DEM by the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1872-1879
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• 2001

As multiview video applications become more popular, correspondence problem for stereo image matching plays an important role in expanding view points. Thus, we propose an efficient dense disparity estimation algorithm considering features of each image pair of multiview image sets. Main concepts of the proposed algorithm are based on the region-dividing-bidirectional-pixel-matching method. This algorithm makes matching process efficient and keeps the reliability of the estimated disparities. Other improvement have obtained by proposed cost function, matching window expanding technique, disparity regularization, and disparity assignment in ambiguous region. These techniques make disparities more stable by removing false disparities and ambiguous regions. The estimated disparities are used to synthesize intermediate views of multiview images. Computer simulation demonstrates the excellence of the proposed algorithm in both subjective and objective evaluations. In addition, processing time is reduced as well.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.311-316
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• 2006

Despite geospatial information systems are widely used in many different fields as a powerful tool for spatial analysis and decision-making, their capabilities to handle realistic 3-D urban environment are very limited. The objective of this work is to integrate the recent developments in 3-D modeling and visualization into GIS to enhance its 3-D capabilities. To achieve a photorealistic view, building models are collected from a pair of aerial stereo images. Roof and wall textures are respectively obtained from ortho-rectified aerial image and ground photography. This study is implemented by using ArcGIS as the work platform and ArcObjects and Visual Basic as development tools. Presented in this paper are 3-D geometric modeling and its data structure, texture creation and its association with the geometric model. As the results, photorealistic views of Purdue University campus are created and rendered with ArcScene.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.121-130
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• 2011

This paper highlights the reconstruction of the rectilinear type of 3D rooftop model from satellite image data using centroid neural network. The main idea of the proposed 3D reconstruction method is based on the grouping of 3D line segments. 3D lines are extracted by 2D lines and DEM (Digital Elevation Map) data evaluated from a pair of stereo images. Our grouping process consists of two steps. We carry out the first grouping process to group fragmented or duplicated 3D lines into the principal 3D lines, which can be used to construct the rooftop model, and construct the groups of lines that are parallel each other in the second step. From the grouping result, 3D rooftop models are reconstructed by the final clustering process. High-resolution IKONOS images are utilized for the experiments. The experimental result's indicate that the reconstructed building models almost reflect the actual position and shape of buildings in a precise manner, and that the proposed approach can be efficiently applied to building reconstruction problem from high-resolution satellite images of an urban area.