• Title/Summary/Keyword: RFM 모형

Search Result 15, Processing Time 0.019 seconds

Development of Modeling Method for 3-D Positioning of IKONOS Satellite Imagery (IKONOS 위성영상의 3차원 위치 결정 모형화 기법 개발)

  • 진경혁;홍재민;유환희;유복모
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
    • /
    • 2004.11a
    • /
    • pp.269-274
    • /
    • 2004
  • Recent adoption of the generalized sensor model to IKONOS and Quickbird satellite imagery have promoted various research activities concerning alternative sensor models which can replace conventional physical sensor models. For example, there are the Rational Function Model(RFM), the Direct Linear Transform(DLT) and the polynomial transform. In this paper, the DLT model which uses just a few number of GCPs was suggested. To evaluate the accuracy of the proposed DLT model, the RFM using 35 GCPs and the bias compensation method(Fraser et al., 2003) were compared with it. Quantitative evaluation of 3B positioning results were performed with independent check points and the digital elevation models(DEMs). In result, a 1.9- to 2.2-m positioning accuracy was achieved for modeling and DEM accuracy is similar to the accuracy of the other model methods.

  • PDF

Comparison Among Sensor Modeling Methods in High-Resolution Satellite Imagery (고해상도 위성영상의 센서모형과 방법 비교)

  • Kim, Eui Myoung;Lee, Suk Kun
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.26 no.6D
    • /
    • pp.1025-1032
    • /
    • 2006
  • Sensor modeling of high-resolution satellites is a prerequisite procedure for mapping and GIS applications. Sensor models, describing the geometric relationship between scene and object, are divided into two main categories, which are rigorous and approximate sensor models. A rigorous model is based on the actual geometry of the image formation process, involving internal and external characteristics of the implemented sensor. However, approximate models require neither a comprehensive understanding of imaging geometry nor the internal and external characteristics of the imaging sensor, which has gathered a great interest within photogrammetric communities. This paper described a comparison between rigorous and various approximate sensor models that have been used to determine three-dimensional positions, and proposed the appropriate sensor model in terms of the satellite imagery usage. Through the case study of using IKONOS satellite scenes, rigorous and approximate sensor models have been compared and evaluated for the positional accuracy in terms of acquirable number of ground controls. Bias compensated RFM(Rational Function Model) turned out to be the best among compared approximate sensor models, both modified parallel projection and parallel-perspective model were able to be modelled with a small number of controls. Also affine transformation, one of the approximate sensor models, can be used to determine the planimetric position of high-resolution satellites and perform image registration between scenes.

Implemental Model of Customer Relationship Management System for Oriental Hospital Using Customer Segmentation (고객세분화를 통한 한방병원 고객관계관리 시스템 구축모형)

  • Ahn, Yo-Chan
    • Journal of Korea Society of Industrial Information Systems
    • /
    • v.15 no.5
    • /
    • pp.79-87
    • /
    • 2010
  • This paper is proposed that implemental model of customer relationship management system for oriental hospital is designed by customer segmentation using personal information and medical record of outpatients in existing integrated medical information system database. Proposed model can be practical model at once, because it can construct by partial modification of existing medical information system without additional information technology and infrastructure. And, if we use the proper variable and method of customer segmentation according to marketing strategy, it can be flexible customer relationship management system not only improvement of customer satisfaction but also various marketing supports.

Surface Reconstruction Using CORONA KH-4 Imagery (CORONA KH-4 영상을 이용한 3차원 지형정보 취득)

  • Sohn, Hong-Gyoo;Yeu, Bock-Mo;Kim, Gi-Hong;Choi, Jong-Hyun
    • 한국지형공간정보학회:학술대회논문집
    • /
    • 2002.03a
    • /
    • pp.145-149
    • /
    • 2002
  • CORONA는 미국이 1960년에서 1972년까지 냉전시대 관심지역에 대한 첩보영상을 취득하기 위하여 운영한 영상취득시스템으로 1995년 일반에 자료가 공개됨에 따라 과거의 고해상도 영상자료를 이용할 수 있는 길이 열리게 되었다. 그러나 현재까지 CORONA 영상처리를 위한 모듈을 제공하는 원격탐측 소프트웨어가 개발되어 있지 않기 때문에 CORONA 영상을 이용하여 수치표고모형이나 정사영상을 제작하기 위해서는 적절한 모델링 방법이 필요하다. CORONA 영상은 파노라마 영상으로 필름 가장자리로 갈수록 왜곡이 많이 생기며 사진기 지표가 없고 위성의 궤도와 위치, 자세, 속도, IMC(Image Motion Compensation)에 대한 자세한 자료를 제공하지 않는 문제점이 있다. 따라서 본 논문에서는 지형복원을 위하여 지상기준점을 이용하는 2가지 모델링 방법을 이용하였다. 첫 번째는 파노라마 왜곡과 촬영 비행체 이동에 의한 왜곡, IMC에 의한 왜곡을 보정하는 모형식을 구성하여 이용하였으며, 두 번째는 위성과 센서에 대한 정보를 필요로 하지 않는 다항식비례모형(RFM; Rational Function Model)을 이용하였다. 대상지역은 서울지역의 입체영상으로 대략 $33km{\times}26km$ 지역이다. 영상은 지상해상도 약 2.7m로 스캐닝하였고 1:1000 수치지도를 통해 20개의 기준점과 36개의 검사점을 관측하였다. 검사점의 위치정확도를 평가해 본 결과 첫 번째 방법은 수평방향으로 평균 3.9m(X), 2.8m(Y)의 오차를 보였으며 표고의 경우 4.2m의 오차를 보여주었다. 두 번째 방법은 수평방향으로 평균 3.2m(X), 2.8m(Y)의 오차를 보였으며 표고의 경우 5.5m의 오차를 보여주었다. 지형복원 정확도를 검증하기 위하여 첫 번째 방법을 이용하여 대상지역 중 일부인 서울 남산지역에 대해 정사영상과 10m간격의 DEM을 제작하였으며 1:1000 수치지도를 통해 제작된 DEM과 비교한 결과 총 43990개 격자점의 표고 차이는 평균 5.98m였다.

  • PDF

3-D Building Reconstruction from Standard IKONOS Stereo Products in Dense Urban Areas (IKONOS 컬러 입체영상을 이용한 대규모 도심지역의 3차원 건물복원)

  • Lee, Suk Kun;Park, Chung Hwan
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.26 no.3D
    • /
    • pp.535-540
    • /
    • 2006
  • This paper presented an effective strategy to extract the buildings and to reconstruct 3-D buildings using high-resolution multispectral stereo satellite images. Proposed scheme contained three major steps: building enhancement and segmentation using both BDT (Background Discriminant Transformation) and ISODATA algorithm, conjugate building identification using the object matching with Hausdorff distance and color indexing, and 3-D building reconstruction using photogrammetric techniques. IKONOS multispectral stereo images were used to evaluate the scheme. As a result, the BDT technique was verified as an effective tool for enhancing building areas since BDT suppressed the dominance of background to enhance the building as a non-background. In building recognition, color information itself was not enough to identify the conjugate building pairs since most buildings are composed of similar materials such as concrete. When both Hausdorff distance for edge information and color indexing for color information were combined, most segmented buildings in the stereo images were correctly identified. Finally, 3-D building models were successfully generated using the space intersection by the forward RFM (Rational Function Model).