• Title/Summary/Keyword: Stereo Satellite Images

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Accuracy Analysis of DEMs Generated from High Resolution Optical and SAR Images (고해상도 광학영상과 SAR영상으로부터 생성된 수치표고모델의 정확도 분석)

  • Kim, Chung;Lee, Dong-Cheon;Yom, Jae-Hong;Lee, Young-Wook
    • 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.

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A Experimental Study on the 3-D Image Restoration Technique of Submerged Area by Chung-ju Dam (충주댐 수몰지구의 3차원 영상복원 기법에 관한 실험적 연구)

  • 연상호
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.1
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    • pp.21-27
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    • 2004
  • It will be a real good news fer the people who were lost their hometown by the construction of a large dam to be restored to the farmer state. Focused on Cheung-pyung around where most part were submerged by the Chungju large Dam founded in eurly 1980s, It used remote sensing image restoration Technique in this study in order to restore topographical features before the flood with stereo effects. We gathered comparatively good satellite photos and remotely sensed digital images, then its made a new fusion image from these various satellite images and the topographical map which had been made before the water filled by the DAM. This task was putting together two kinds of different timed images. And then, we generated DEM including the outskirts of that area as matching current contour lines with the map. That could be a perfect 3D image of test areas around before when it had been water filled by making perspective images from all directions included north, south, east and west, fer showing there in 3 dimensions. Also, for close range visiting made of flying simulation can bring to experience their real space at that time. As a result of this experimental task, it made of new fusion images and 3-D perspective images and simulation live images by remotely sensed photos and images, old paper maps about vanished submerged Dam areas and gained of possibility 3-D terrain image restoration about submerged area by large Dam construction.

Reconstruction of 3D Building Model from Satellite Imagery Based on the Grouping of 3D Line Segments Using Centroid Neural Network (중심신경망을 이용한 3차원 선소의 군집화에 의한 위성영상의 3차원 건물모델 재구성)

  • Woo, Dong-Min;Park, Dong-Chul;Ho, Hai-Nguyen;Kim, Tae-Hyun
    • 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.

Improving the Accuracy of 3D Object-space Data Extracted from IKONOS Satellite Images - By Improving the Accuracy of the RPC Model (IKONOS 영상으로부터 추출되는 3차원 지형자료의 정확도 향상에 관한 연구 - RPC 모델의 위치정확도 보정을 통하여)

  • 이재빈;곽태석;김용일
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.21 no.4
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    • pp.301-308
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    • 2003
  • This study describes the methodology that improves the accuracy of the 3D object-space data extracted from IKONOS satellite images by improving the accuracy of a RPC(Rational Polynomial Coefficient) model. For this purpose, we developed the algorithm to adjust a RPC model, and could improve the accuracy of a RPC model with this algorithm and geographically well-distributed GCPs(Ground Control Points). Furthermore, when a RPC model was adjusted with this algorithm, the effects of geographic distribution and the number of GCPs on the accuracy of the adjusted RPC model was tested. The results showed that the accuracy of the adjusted RPC model is affected more by the distribution of GCPs than by the number of GCPs. On the basis of this result, the algorithm using pseudo_GCPs was developed to improve the accuracy of a RPC model in case the distribution of GCPs was poor and the number of GCPs was not enough to adjust the RPC model. So, even if poorly distributed GCPs were used, the geographically adjusted RPC model could be obtained by using pseudo_GCPs. The less the pseudo_GCPs were used -that is, GCPs were more weighted than pseudo_GCPs in the observation matrix-, the more accurate the adjusted RPC model could be obtained, Finally, to test the validity of these algorithms developed in this study, we extracted 3D object-space coordinates using RPC models adjusted with these algorithms and a stereo pair of IKONOS satellite images, and tested the accuracy of these. The results showed that 3D object-space coordinates extracted from the adjusted RPC models was more accurate than those extracted from original RPC models. This result proves the effectiveness of the algorithms developed in this study.

Extracting DEM Using Kompsat Images (Kompsat 영상을 이용한 수치표고모델추출)

  • Choi, Hyun;Kang, In-Joon;Hong, Soon-Heun
    • Journal of Korean Society for Geospatial Information Science
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    • v.10 no.3 s.21
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    • pp.71-77
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    • 2002
  • DEMs(digital elevation models) are generally used to automatically map the channel network and to delineate subbasins. At present, most DEM data are derived from three alternative sources which are ground survey, pphotogrammetric data capture and digitized cartographic data sources. The accuracy of a DEM is dependent on the spatial resolution, quality of the source data, collection and processing procedures, and digitizing systems. weather conditions and nature environment.etc provide us satellite image of the highest quality. However, Match in error of the auto generation DEM was severely affected by physical and environmental conditions at shooting time. This paper shows that real-time operation analysis of applied hydrology after extracting DEM Using a pair of Kompsat images.

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Evaluation on Tie Point Extraction Methods of WorldView-2 Stereo Images to Analyze Height Information of Buildings (건물의 높이 정보 분석을 위한 WorldView-2 스테레오 영상의 정합점 추출방법 평가)

  • Yeji, Kim;Yongil, Kim
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.5
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    • pp.407-414
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    • 2015
  • Interest points are generally located at the pixels where height changes occur. So, interest points can be the significant pixels for DSM generation, and these have the important role to generate accurate and reliable matching results. Manual operation is widely used to extract the interest points and to match stereo satellite images using these for generating height information, but it causes economic and time consuming problems. Thus, a tie point extraction method using Harris-affine technique and SIFT(Scale Invariant Feature Transform) descriptors was suggested to analyze height information of buildings in this study. Interest points on buildings were extracted by Harris-affine technique, and tie points were collected efficiently by SIFT descriptors, which is invariant for scale. Searching window for each interest points was used, and direction of tie points pairs were considered for more efficient tie point extraction method. Tie point pairs estimated by proposed method was used to analyze height information of buildings. The result had RMSE values less than 2m comparing to the height information estimated by manual method.

A Hybrid Approach for Automated Building Area Extraction from High-Resolution Satellite Imagery (고해상도 위성영상을 활용한 자동화된 건물 영역 추출 하이브리드 접근법)

  • An, Hyowon;Kim, Changjae;Lee, Hyosung;Kwon, Wonsuk
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.6
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    • pp.545-554
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    • 2019
  • This research aims to provide a building area extraction approach over the areas where data acquisition is impossible through field surveying, aerial photography and lidar scanning. Hence, high-resolution satellite images, which have high accessibility over the earth, are utilized for the automated building extraction in this study. 3D point clouds or DSM (Digital Surface Models), derived from the stereo image matching process, provides low quality of building area extraction due to their high level of noises and holes. In this regards, this research proposes a hybrid building area extraction approach which utilizes 3D point clouds (from image matching), and color and linear information (from imagery). First of all, ground and non-ground points are separated from 3D point clouds; then, the initial building hypothesis is extracted from the non-ground points. Secondly, color based building hypothesis is produced by considering the overlapping between the initial building hypothesis and the color segmentation result. Afterwards, line detection and space partitioning results are utilized to acquire the final building areas. The proposed approach shows 98.44% of correctness, 95.05% of completeness, and 1.05m of positional accuracy. Moreover, we see the possibility that the irregular shapes of building areas can be extracted through the proposed approach.

Correction of Geometric Distortion of Internet Aerial Imagery and Photo-Realistic 3D Building Modeling (인터넷 항공영상의 왜곡보정과 실감적 3차원 건물 모델링)

  • Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.29 no.6
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    • pp.687-695
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    • 2011
  • Many internet portals provide maps with spatial information services. Recently, various images including aerial, satellite, street view, and photo-realistic 3D city models are provided as well as maps. This study suggested a method for geometric correction of the panoramic aerial images in the internet portal and 3D building modeling using information which is available in the internet. The key of this study is to obtain all necessary data easily from internet without restrictions. Practically, the ground control coordinates could be available from geo-referenced internet maps, and stereo pairs of the aerial images and close-range photographs for photo-realistic object modeling are provided by the internet service. However, the ground control points are not suitable for accurate mapping. RMSE of the plotting was about 9 meters and reduced upto 4 meters after coordinate transformation. The proposed methods would be applicable to various applications of photo-realistic object modeling which do not require high accuracy.

Automatic Measuring of GCP's Image Coordinates using Control Point Patch and Auxiliary Points Matching (기준점 패치 및 보조점 정합에 의한 지상기준점의 영상좌표 자동관측)

  • Kang, Myung-Ho;Bang, Soo-Nam;Lee, Yong-Woong
    • Journal of Korean Society for Geospatial Information Science
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    • v.11 no.2 s.25
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    • pp.29-37
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    • 2003
  • An approach is described for automatic measuring of GCP's image coordinates from SPOT imagery and focused on the fulfillment an automatic orientation of satellite images. For the orientation of a stereopair of digital images, firstly, GCP(Ground Control Point) should be selected and then the work for measuring of image coordinates correspond to GCPs is required. In this study, we propose the method for extracting the GCP's image coordinates automatically using an image patch for control points and auxiliary points matching. For the evaluation of measurement accuracy, a comparison between points those are extracted manually and automatically by a proposed method have made. Finally, we shows the feasibility of automatic image coordinates measurment by applying in stereo modeling for SPOT images.

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A Study on the Fusion of DEM Generated from Images of Optical Satellite and SAR (광학 위성영상과 SAR 위성영상의 DEM 융합에 관한 연구)

  • Yeu, Bock-Mo;Hong, Jae-Min;Jin, Kyeong-Hyeok;Yoon, Chang-Rak
    • 한국지형공간정보학회:학술대회논문집
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    • 2002.11a
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    • pp.58-65
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    • 2002
  • The most widespread techniques for DEM generation are stereoscopy for optical sensor images and interfereometry for SAR images. These techniques suffer from certain sensor and processing limitations, which can be overcome by the synergetic use of both sensors and DEMs respectively. In this paper, different strategies for fusing SAR and optical data are combined to derive high quality DEM products. The multiresolution wavelet transform, which take advantage of the complementary properties of SAR and stereo optical DEMs, will be applied for the fusion process. By taking advantage of the fact that errors of the DEMs are of different nature using the multiresolution wavelet transform, affected part are filtered and replaced by those of the counterpart and is tested with two sets of SPOT and ERS DEM, resulting in a remarkable improvement in DEM. For the analysis of results, the reference DEM is generated from digital base map(1:5000).

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