KSCE Journal of Civil and Environmental Engineering Research (대한토목학회논문집)

Korean Society of Civil Engeneers (대한토목학회)
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Automated Satellite Image Co-Registration using Pre-Qualified Area Matching and Studentized Outlier Detection

사전검수영역기반정합법과 't-분포 과대오차검출법'을 이용한 위성영상의 '자동 영상좌표 상호등록'

  • 김종홍 (연세대학교 사회환경시스템공학부) ;
  • 허준 (연세대학교 사회환경시스템공학부) ;
  • 손홍규 (연세대학교 사회환경시스템공학부)
  • Received : 2005.10.10
  • Accepted : 2005.12.22
  • Published : 2006.07.31
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Abstract

Image co-registration is the process of overlaying two images of the same scene, one of which represents a reference image, while the other is geometrically transformed to the one. In order to improve efficiency and effectiveness of the co-registration approach, the author proposed a pre-qualified area matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with cross correlation coefficient. For refining matching points, outlier detection using studentized residual was used and iteratively removes outliers at the level of three standard deviation. Throughout the pre-qualification and the refining processes, the computation time was significantly improved and the registration accuracy is enhanced. A prototype of the proposed algorithm was implemented and the performance test of 3 Landsat images of Korea. showed: (1) average RMSE error of the approach was 0.435 pixel; (2) the average number of matching points was over 25,573; (3) the average processing time was 4.2 min per image with a regular workstation equipped with a 3 GHz Intel Pentium 4 CPU and 1 Gbytes Ram. The proposed approach achieved robustness, full automation, and time efficiency.

최근 전 지구적, 혹은 대규모 지역의 분석 및 모니터링을 위한 위성영상의 사용이 늘어나고 있으며 이를 처리하기 위해 빠르고 편리한 '영상좌표 상호등록'방법이 요구되고 있다. 이러한 '영상좌표 상호등록'은 위성의 센서모델 및 천체력 자료를 이용하는 엄밀 모델식을 이용하는 방법과 기 존재하는 기준 영상(Reference image)을 사용하거나 혹은 수치지도를 사용하는 경험적 방법의 두 가지로 분류할 수 있다. '영상좌표 상호등록'의 효율성을 높이기 위해서 저자는 '사전검수 영역기반정합법'(Pre-qualified area matching)을 사용하였다. 이는 Canny 연산자를 이용한 경계추출법, 교차상관계수를 사용한 영역기반정합법(Area based matching), t-분포를 이용하여 95%의 신뢰구간 내에서 과대오차 소거법을 적용한 방법이다. 이러한 사전검수(Pre-qualification) 과정을 통해 연산시간을 현저히 단축시켰고, '영상좌표 상호등록'의 정확도 역시 향상됨을 알 수 있었다. 제안한 알고리즘을 사용하여 프로그램을 작성하고, 한반도 Landsat ETM+ 영상 3장을 이용하여 테스트하였다. 정합점 간의 평균제곱오차는 0.435 영상소, 정합점은 평균 25,573개로 나타났다. 연산 시간은 3.0GHz 1Gb RAM 사양의 컴퓨터에서 평균 약 4.2분으로 나타났다.

Keywords

References

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