• Title/Summary/Keyword: 영상 GCP

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Quality Analysis of GCP Chip Using Google Map (Google Map을 이용한 GCP 칩의 품질 분석)

  • Park, Hyeongjun;Son, Jong-Hwan;Shin, Jung-Il;Kweon, Ki-Eok;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.35 no.6_1
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    • pp.907-917
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    • 2019
  • Recently, the demand for high-resolution satellite images increases in many fields such as land monitoring and terrain analysis. Therefore, the need for geometric correction is increasing. As an automatic precision geometric correction method, there is a method of automatically extracting the GCP by matching between the GCP Chip and the satellite image. For automatic precision geometric correction, the success rate of matching GCP Chip and satellite image is important. Therefore, it is important to evaluate the matching performance of the manufactured GCP Chip. In order to evaluate the matching performance of GCP Chips, a total of 3,812 GCP Chips in South Korea were used as experimental data. The GCP Chip matching results of KOMPSAT-3A and Google Map showed similar matching results. Therefore, we determined that Google Map satellite imagery could replace high-resolution satellite imagery. Also, presented a method using center point and error radius of Google Map to reduce the time required to verify matching performance. As a result, it is best to set the optimum error radius to 8.5m. Evaluated the matching performance of GCP Chips in South Korea using Google Maps. And verified matching result using presented method. As a result, the GCP Chip s in South Korea had a matching success rate of about 94%. Also, the main matching failure factors were analyzed by matching failure GCP Chips. As a result, Except for GCP Chips that need to be remanufactured, the remaining GCP Chips can be used for the automatic geometric correction of satellite images.

Construction, Search of Ground Control Point Database and its Application for Satellite Image Correction (위성영상 보정을 위한 GCP 데이터베이스 구축, 검색 및 활용)

  • Lee, Young-Ran;Shin, Dongseok;Lee, Hae-Yeoun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.1 no.1
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    • pp.8-17
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    • 1998
  • This paper presents a method of construction and re-use of a GCP database for precision geometric correction of high resolution satellite images. Accurate geometric correction can be achieved by using accurate GCPs. The GCP information which is extracted from maps or other sources is saved in a database in conjunction with the corresponding image chips. The usage of the GCPs from the database gives reusability and efficiency in marking new GCPs. An image matching algorithm was developed to determine the corresponding positions between an image chip and a new image. The proposed technique can save time in the regular operation of satellite image preprocessing by propagating the pre-determined GCPs to the new image correction.

Development of the Precision Image Processing System for CAS-500 (국토관측위성용 정밀영상생성시스템 개발)

  • Park, Hyeongjun;Son, Jong-Hwan;Jung, Hyung-Sup;Kweon, Ki-Eok;Lee, Kye-Dong;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.36 no.5_2
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    • pp.881-891
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    • 2020
  • Recently, the Ministry of Land, Infrastructure and Transport and the Ministry of Science and ICT are developing the Land Observation Satellite (CAS-500) to meet increased demand for high-resolution satellite images. Expected image products of CAS-500 includes precision orthoimage, Digital Surface Model (DSM), change detection map, etc. The quality of these products is determined based on the geometric accuracy of satellite images. Therefore, it is important to make precision geometric corrections of CAS-500 images to produce high-quality products. Geometric correction requires the Ground Control Point (GCP), which is usually extracted manually using orthoimages and digital map. This requires a lot of time to acquire GCPs. Therefore, it is necessary to automatically extract GCPs and reduce the time required for GCP extraction and orthoimage generation. To this end, the Precision Image Processing (PIP) System was developed for CAS-500 images to minimize user intervention in GCP extraction. This paper explains the products, processing steps and the function modules and Database of the PIP System. The performance of the System in terms of processing speed, is also presented. It is expected that through the developed System, precise orthoimages can be generated from all CAS-500 images over the Korean peninsula promptly. As future studies, we need to extend the System to handle automated orthoimage generation for overseas regions.

A Study on the GCP and DEM Accuracy Evaluation of SPOT Image Using GPS (GPS를 이용한 SPOT 영상의 GCP 및 DEM 정확도 평가)

  • 윤희천;이용욱
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.1
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    • pp.73-80
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    • 2004
  • The purpose of this study is the GCP/DEM estimations through satellite stereo image interpretation using GPS. We carried out GPS observation fixing first order control points and GPS permanent stations. Comparing static surveying and kinematic surveying, we analysed the surveying methods for GCP and DEM estimations. As the results, considering SPOT image spatial resolution, the DEM can be made through satellite stereo image interpretation.

GCP Chip Automatic Extraction of Satellite Imagery Using Interest Point in North Korea (특징점 추출기법을 이용한 접근불능지역의 위성영상 GCP 칩 자동추출)

  • Lee, Kye Dong;Yoon, Jong Seong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.4
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    • pp.211-218
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    • 2019
  • The Ministry of Land, Infrastructure and Transport is planning to launch CAS-500 (Compact Advanced Satellite 500) 1 and 2 in 2019 and 2020. Satellite image information collected through CAS-500 can be used in various fields such as global environmental monitoring, topographic map production, analysis for disaster prevention. In order to utilize in various fields like this, it is important to get the location accuracy of the satellite image. In order to establish the precise geometry of the satellite image, it is necessary to establish a precise sensor model using the GCP (Ground Control Point). In order to utilize various fields, step - by - step automation for orthoimage construction is required. To do this, a database of satellite image GCP chip should be structured systematically. Therefore, in this study, we will analyze various techniques for automatic GCP extraction for precise geometry of satellite images.

Determination of Spatial Resolution to Improve GCP Chip Matching Performance for CAS-4 (농림위성용 GCP 칩 매칭 성능 향상을 위한 위성영상 공간해상도 결정)

  • Lee, YooJin;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1517-1526
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    • 2021
  • With the recent global and domestic development of Earth observation satellites, the applications of satellite images have been widened. Research for improving the geometric accuracy of satellite images is being actively carried out. This paper studies the possibility of automated ground control point (GCP) generation for CAS-4 satellite, to be launched in 2025 with the capability of image acquisition at 5 m ground sampling distance (GSD). In particular, this paper focuses to check whether GCP chips with 25 cm GSD established for CAS-1 satellite images can be used for CAS-4 and to check whether optimalspatial resolution for matching between CAS-4 images and GCP chips can be determined to improve matching performance. Experiments were carried out using RapidEye images, which have similar GSD to CAS-4. Original satellite images were upsampled to make satellite images with smaller GSDs. At each GSD level, up-sampled satellite images were matched against GCP chips and precision sensor models were estimated. Results shows that the accuracy of sensor models were improved with images atsmaller GSD compared to the sensor model accuracy established with original images. At 1.25~1.67 m GSD, the accuracy of about 2.4 m was achieved. This finding lead that the possibility of automated GCP extraction and precision ortho-image generation for CAS-4 with improved accuracy.

Estimating Accuracy of 3-D Models of SPOT Imagery Based on Changes of Number of GCPs (SPOT영상을 사용한 3차원 모델링시 지상기준점수에 따른 정확도 평가)

  • 김감래;안병구;김명배
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.21 no.1
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    • pp.61-69
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    • 2003
  • There is various kinds cause that influence to created DEM and orthoimage using stereo satellite images. Specialty, research about effect that GCP number gives to accuracy of DEM, orthoimage and modeling may have to be gone ahead. Therefore, this research increases GCP number by 5 to 30 and created each modeling, DEM and orthoimage using SPOT panchromatic images that resolution is 10m by digital image processing method. Accuracy assessment did by orthoimage using 20 check point. As a result, GCP number between 10∼30 modeling RMSE is 1 pixel low appear. Horizontal·vertical error that use orthoimage looked tendency that decrease GCP number increases, and confirmed by the most economical in GCP number 10∼15. Also, analyze correlation of GCP number and orthoimage position accuracy and presented improvement plan and research task hereafter.

Quality Assessment of Digital Surface Model Vertical Position Accuracies by Ground Control Point Location (지상기준점 선점 위치에 따른 DSM 높이 정확도 분석)

  • Lee, Jong Phil
    • Journal of Cadastre & Land InformatiX
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    • v.51 no.1
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    • pp.125-136
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    • 2021
  • Recently, Unmanned Aerial Vehicle utilization and image processing technology for remote sensing have diversified remarkably with Orthophoto and Digital Surface Model. In particular, It uses more application fields such as spatial information analysis and hazardous areas as well as land surveying. This study analyses the accuracy of the coordinate on Orthophoto and DSM height on slope area with high and low differences by using UAV images. As the result of this study, in the case of GCP on 2D orthophoto, the location error was not produced significantly. The vertical position of the DSM showed the highest accuracy when the height difference between GCPs is under 30m(RMSEZ=0.07m). The location of the GCPs was divided into approximately 10m, 20m, 30m, and 40m with analysis for each of the eight points of GCP and inspection points in general. This study expects that producing both horizontal accuracy of Orthophoto and vertical accuracy of DSM using UAV on the sloped area which similar to this research area will help in spatial information fields.

The Study of the Geometric Structure Optimization for the Stereo X-ray Inspection System Using the Calibration (Calibration을 통한 스테레오 X-ray 검색장치의 기하구조 최적화 연구)

  • Hwang, Young-Gwan;Lee, Nam-Ho;Lee, Seung-Min;Park, Jong-Won
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.9
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    • pp.3422-3427
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    • 2010
  • In this paper, we presents a sensor calibration technique using stereo X-ray images to provide efficient inspection of fast moving cargo objects. Stereo X-ray scanned images are acquired from a specially designed equipment which consists of a X-ray source, dual-linear array detector, and a conveyor system. Dual detector is installed so that rectified stereo X-ray images of objects are acquired. Using the stereo X-ray images, we carry out a sensor calibration to find the correspondences between the images and reconstruct 3-D shapes of real objects. Using the Image acquired from the stereo detectors with varying distances, we calculated the GCP(ground control point)of the image. And we figure out the error by comparing calculated GCP and GCP of the real object. The experimental results show the proposed technique can enhance the accuracy of stereo matching and give more efficient visualization for cargo inspection image.

수치지도를 이용한 EOC영상의 반자동 기하보정

  • 안석범;박찬용;최준수;한광수;김천
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.04a
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    • pp.575-580
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    • 2003
  • KOMPSAT-1 위성의 EOC영상은 위성에서 지구를 촬영하는 동안 발생하는 영상 왜곡을 포함하고 있다. 본 연구는 EOC영상의 영상왜곡을 보정하기 위하여 수치지도를 이용하는 정밀기하보정에 대하여 연구한다. 정밀기하보정 과정은 수치지도와 EOC영상의 좌표계를 통합하는 과정을 거쳐 오버레이를 만들어 수치지도의 삼각점을 기준으로 위성영상에서 GCP를 선택하고, 이 GCP를 이용하여 위성 영상을 딜로니 삼각형들의 Mesh형태로 변환하여 모든 딜로니 삼각형을 리샘플링하는 과정을 거쳐 보정된 EOC영상을 얻는다.

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