• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.2
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• pp.117-132
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• 2014

This paper had a purpose on analyzing result data from pan-sharpening, which have applied on the KOMPSAT-2 and -3 image. Particularly, the study focused on comparing each relative spectral response functions, which considers to cause color distortions of fused image. Two images from same time and location have been collected by KOMPSAT-2 and -3 to apply in the experiment. State-of-the-art algorithms of GIHS, GS1, GSA and GSA-CA were employed for analyzing the results in quantitatively and qualitatively. Following analysis of previous studies, GSA and GSA-CA methods resulted excellent quality in both of KOMPSAT-2/3 results, since they minimize spectral discordances between intensity and PAN image by the linear regression algorithm. It is notable that performances from KOMPSAT-2 and- 3 are not equal under same circumstances because of different spectral characteristics. In fact, KOMPSAT-2 is known as over-injection of low spatial resolution components of blue and green band, are greater than that of the PAN band. KOMPSAT-3, however, has been advanced in most of misperformances and weaknesses comparing from the KOMPSAT-2.

• Bulletin of the Korean Space Science Society
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• 2003.10a
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• pp.97-97
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• 2003

아리랑위성 1호는 1999년 12월 21일 발사되어 3년의 설계 임무 수명을 성공적으로 완료하였으며 현재 위성체의 특이한 이상 상태 없이 안정적으로 연장 운영되고 있다. 위성이 성공적으로 임무를 수행하기 위해서는 태양전지 및 배터리 등의 기능이 적절하게 유지되어야 한다. 위성의 전력을 생산하는 태양 전지는 여러 가지 복사 및 운영중의 온도차와 같은 우주환경 등에 의해서 서서히 성능이 감소하게 되고, 배터리 또한 온도상승 등으로 인해서 성능이 감소하게 된다. 또한 위성의 궤도평면과 태양 벡터 사이의 각으로 정의되는 베타각($\beta$)에 의해서 식기간의 변화 및 온도 변화로 인해서 전력계에도 변화가 발생한다. 본 논문에서는 정상운영 초기부터 현재까지 실제 운영 궤도상에서 얻어진 원격계측자료(Telemetry)를 이용하여 전력계의 주요 부분 변화를 살펴보았다.

• Aerospace Engineering and Technology
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• v.13 no.1
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• pp.174-183
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• 2014

The Value-Added Processing System(VAPS) was developed for post-processing the KOMPSAT imagery. Recently software version and hardware specification of VAPS were changed for improving the VAPS performance. The purpose of this study is to describe about the improvement of existing VAPS(ver.1.0) and systematically evaluate the performance of the improved VAPS(ver.2.0). To this end, test-bed areas in South and North Korea were selected and then image processing tests were conducted using KOMPSAT-2 and KOMPSAT-3 imagery in both areas. In conclusion, VAPS(ver.2.0) had an ability to generate the high level products like ortho images and mosaic images. Image processing time using the Graphic Processing Unit(GPU) on ver.2.0 was enhanced up to 10 times than ver.1.0.

• Economic and Environmental Geology
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• v.45 no.4
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• pp.377-384
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• 2012

The main field component of the Earth's magnetic field was modeled from the tri-axial magnetometer onboard KOrean MultiPurpose SATellite-II (KOMPSAT-II) for the purpose of satellite attitude control. The model computed by the KOMPSAT-II magnetometer measurement data is compared with the International Geomagnetic Reference Field (IGRF) model of a degree of up to 13 in spherical harmonic coefficients. The previous study with KOMPSAT-I (Kim et al. 2004) indicated a good correlation of power spectrum of spherical harmonic coefficients with respect to the degree up to 5. This study, however, showed an agreement of the degree up to 8-9 of the coefficient power spectrum and a discrepancy between degrees 10 and 13. We have concluded that relevant data selection process, removal of the external field from the data in the high latitude region, an accuracy of the magnetometer all play an important role in finding a coherence with the IGRF model. This study will be extended to the secular variation model of geomagnetism if longer-period data become available.

• Journal of Astronomy and Space Sciences
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• v.24 no.4
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• pp.297-308
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• 2007

The AOPOD (Atmosphere Occultation and Precision Orbit Determination) system, the secondary payload of KOMPSAT (KOrea Multi-Purpose SATellite)-5 scheduled to be launched in 2010, shall provide GPS radio occultation data. In this paper, we simulated the GPS radio occultation characteristic of KOMPSAT-5 and retrieved electron density profiles using KROPS (KASI Radio Occultation Processing Software). The electron density retrieved from CHAMP (CHAllenging Minisatellite Payload) GPS radio occultation data on June 20, 2004 was compared with IRI (International Reference Ionosphere) - 2001, PLP (Planar Langmuir Probe), and ionosonde measurements. When the result was compared with ionosonde measurements, the discrepancies were 5 km on the $F_2$ peak height ($hmF_2$) and $3{\times}10^{10}el/m^3$ on the electron density of the $F_2$ peak height ($NmF_2$). By comparing with the Laugmuir Probe measurements of CHAMP satellite (PLP), both agrees with $1.6{\times}10^{11}el/m^3$ at the height of 365.6 km.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.319-326
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• 2014

The accurate geo-referencing processes that apply ground control points is prerequisite for effective end use of HRSI (High-resolution satellite imagery). Since the conventional control point acquisition by human operator takes long time, demands for the automated matching to existing reference data has been increasing its popularity. Among many options of reference data, the airborne LiDAR (Light Detection And Ranging) data shows high potential due to its high spatial resolution and vertical accuracy. Additionally, it is in the form of 3-dimensional point cloud free from the relief displacement. Recently, a new matching method between LiDAR data and HRSI was proposed that is based on the image projection of whole LiDAR data into HRSI domain, however, importing and processing the large amount of LiDAR data considered as time-consuming. Therefore, we wmotivated to ere propose a local LiDAR chip generation for the HRSI geo-referencing. In the procedure, a LiDAR point cloud was rasterized into an ortho image with the digital elevation model. After then, we selected local areas, which of containing meaningful amount of edge information to create LiDAR chips of small data size. We tested the LiDAR chips for fully-automated geo-referencing with Kompsat-2 and Kompsat-3 data. Finally, the experimental results showed one-pixel level of mean accuracy.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.91-94
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• 2017

본 연구에서는 Component-Substitution (CS)기반 영상 융합 방법 중 가장 빠른 처리 속도를 보이는 IHS 기법의 분광 왜곡 현상을 해결하기 위하여 히스토그램을 통해 분광 왜곡 현상을 분석하고 평균 필터링을 통해 분광 왜곡 현상을 해결한다. 제안하는 방법의 성능 평가를 위하여 아리랑 3 호로 촬영한 서울 지역 위성 영상에 IHS 방법과 제안하는 방법을 적용하여 주관적으로 비교하고 객관적으로는 Q4, SAM, ERGAS 의 지표를 사용하여 비교한다. 주관적 비교 결과 제안하는 방법이 분광 왜곡을 감소시킴을 보이며, 객관적 비교 결과 IHS 기법 대비 향상된 Q4, SAM, ERGAS 을 보인다.

• Aerospace Engineering and Technology
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• v.3 no.2
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• pp.7-10
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• 2004

KOMPSAT-2 needs fine accuracy attitude control when it is operated in Science mode. Reaction Wheel is a necessary part of fine controlling the attitude of satellite. The reaction Wheel Assembly(RWA) is a device which provides reaction torque for attitude-control of spacecraft. It consists of an electric motor, a rotating flywheel, motor control device electrics, commutation electronics and associated power converters. This document identifies what activities to be carried out to integrate the RW#1 for ETB tests.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.300-304
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• 2020

본 논문에서는 원격 탐사 영상 정합에서 정확도는 유지하면서 특징점 매칭 (Matching) 복잡도를 줄이기 위해 입력 영상을 전처리하는 구조물 검출 네트워크를 이용한 원격 탐사 영상 정합 방법을 제안한다. 영상 정합의 기존 방법은 입력 영상에서 특징점을 추출하고 설명자 (Descriptor)를 생성한다. 본 논문에서 제안하는 방법은 입력 영상에서 특징점 매칭에 영향을 미치는 구조물만 추출하여 새로운 영상을 만들어 특징점을 추출한다. 추출된 특징점은 필터링 (Filtering)을 거쳐 원본 영상에 매핑 (Mapping)되어 설명자를 생성하여 특징점 매칭 속도를 향상시킨다. 또한 구조물 검출 네트워크에서 학습 영상과 시험 영상의 특성의 차이로 생기는 성능 저하 문제를 개선하기 위해 히스토그램 매핑 기법을 이용한다. 아리랑 3 호가 획득한 원격 탐사 영상에 대한 실험을 통해 제안하는 방법은 정확도를 유지하면서 계산 시간을 SURF 보다 87.5%, SIFT 보다 92.6% 감소시킬 수 있다.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.206-214
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• 2022

The way to measure the extent of damage from floods and droughts is to identify changes in the extent of water systems. In order to effectively grasp this at a glance, satellite images are used. KOMPSAT-5 uses Synthetic Aperture Radar (SAR) to capture images regardless of weather conditions such as clouds and rain. In this paper, various deep learning models are applied to perform semantic segmentation of the water system in this SAR image and the performance is compared. The models used are U-net, V-Net, U2-Net, UNet 3+, PSPNet, Deeplab-V3, Deeplab-V3+ and PAN. In addition, performance comparison was performed when the data was augmented by applying elastic deformation to the existing SAR image dataset. As a result, without data augmentation, U-Net was the best with IoU of 97.25% and pixel accuracy of 98.53%. In case of data augmentation, Deeplab-V3 showed IoU of 95.15% and V-Net showed the best pixel accuracy of 96.86%.