한국측량학회지 (Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography)

  • 제40권4호
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  • Pages.293-304
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  • 2022
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  • 1598-4850(pISSN)
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  • 2288-260X(eISSN)
한국측량학회 (Korean Society of Surveying, Geodesy, Photogrammetry and Cartography)
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KOMPSAT-3 위성영상의 상대기하보정에 대한 건물의 영향 분석

Impact Analysis of Buildings for KOMPSAT-3 Image Co-registration

  • Park, Jueon (Dept. of Civil Engineering, Seoul National University of Science and Technology) ;
  • Kim, Taeheon (Dept. of Civil Engineering, Seoul National University of Science and Technology) ;
  • Yun, Yerin (Dept. of Civil Engineering, Seoul National University of Science and Technology) ;
  • Lee, Chabin (Dept. of Civil Engineering, Seoul National University of Science and Technology) ;
  • Lee, Jinmin (Dept. of Civil Engineering, Seoul National University of Science and Technology) ;
  • Lee, Changno (Dept. of Civil Engineering, Seoul National University of Science and Technology) ;
  • Han, Youkyung (Dept. of Civil Engineering, Seoul National University of Science and Technology)
  • 투고 : 2022.07.29
  • 심사 : 2022.08.23
  • 발행 : 2022.08.31
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초록

본 연구에서는 고해상도 위성영상의 상대기하보정 결과에 건물이 미치는 영향을 분석하기 위해 건물에서 추출된 정합쌍의 유무에 따른 상대기하보정 결과를 비교한다. 건물 정합쌍의 제거를 위해 수치지형도에서 건물 객체를 추출하여 생성한 건물마스크 영상을 이용하였으며, 추가적으로 수렴각의 크기에 따른 정합쌍 추출 성능 및 상대기하보정 결과를 분석하였다. Affine 및 Piecewise linear 변환모델을 각각 적용하여 건물밀집지역에 대한 상대기하보정 결과를 비교하였다. 실험 결과, Affine 변환모델은 건물 정합쌍 제거 후 전반적인 정확도 향상을 나타내었다. 반면에, Piecewise linear 변환모델은 주변에 건물을 포함하고 있는 검사점에서 정확도가 향상되었으나, 건물이 없는 평탄한 지역의 검사점에서는 정확도 향상이 크지 않았다. 또한, Piecewise linear 변환모델을 적용할 경우 20° 이하의 수렴각을 갖는 영상에서 2 pixels 이하의 안정적인 정확도를 도출하였다.

In this study, to analyze the effect of buildings on the image co-registration performance, co-registration results are compared according to the presence or absence of matching points extracted from buildings. To remove the matching points extracted from buildings, a building mask generated by extracting building objects from the digital topographic map was used. In addition, matching points extraction performance and image co-registration accuracy were analyzed according to the magnitude of the convergence angle. Image co-registration results were compared by applying the affine and piecewise linear transformation models, respectively. According to the experimental results, the affine transformation model showed an overall improvement in accuracy after removing the matching points extracted from buildings. On the other hand, the piecewise linear transformation model improved the accuracy at the checkpoints including the surrounding buildings, but the accuracy improvement was not significant at checkpoints in the flat area without the existence of buildings. In addition, when the piecewise linear transformation model was applied, stable accuracy of less than 2 pixels was derived from images with a convergence angle of 20° or less.

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과제정보

이 논문은 2022년도 정부(국토교통부)의 재원으로 국토교통과학기술진흥원의 지원을 받아 수행된 연구임(과제번호 RS-2022-00155763).

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