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

Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회)
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Image Registration of Drone Images through Association Analysis of Linear Features

선형정보의 연관분석을 통한 드론영상의 영상등록

  • Received : 2017.09.12
  • Accepted : 2017.12.14
  • Published : 2017.12.31
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Abstract

Drones are increasingly being used to investigate disaster damage because they can quickly capture images in the air. It is necessary to extract the damaged area by registering the drones and the existing ortho-images in order to investigate the disaster damage. In this process, we might be faced the problem of registering two images with different time and spatial resolution. In order to solve this problem, we propose a new methodology that performs initial image transformation using line pairs extracted from images and association matrix, and final registration of images using linear features to refine the initial transformed result. The applicability of the newly proposed methodology in this study was evaluated through experiments using artifacts and the natural terrain areas. Experimental results showed that the root mean square error of artifacts and the natural terrain was 1.29 pixels and 4.12 pixels, respectively, and relatively high accuracy was obtained in the region with artifacts extracted a lot of linear information.

드론은 항공에서 영상을 신속하게 촬영할 수 있기 때문에 재난 피해조사에 활용도가 높아지고 있다. 재난 피해조사를 위해서 드론영상과 기존의 정사영상을 상호 등록하여 피해면적을 추출해야 되는데 이 과정에서 시.공간해상도가 다른 두 영상을 등록해야 하는 문제에 직면하게 된다. 이러한 문제를 해결하기 위해 본 연구에서는 드론영상과 기존의 정사영상에서 추출한 선형쌍과 연관행렬을 이용하여 초기 영상변환을 수행하고, 초기 영상변환 된 결과를 정제하기 위해 선형을 이용하여 영상을 최종 등록하는 새로운 방법론을 제안하였다. 제안한 방법론의 적용성을 평가하기 위해 인공지물이 있는 지역과 자연지역을 구분하여 실험을 수행하였다. 실험결과 인공지물과 자연지역에서 평균제곱근오차는 각각 1.29 픽셀과 4.12 픽셀로 나타났으며, 선형정보를 많이 추출할 수 있는 인공지물이 있는 지역에서 상대적으로 높은 정확도의 결과를 얻을 수 있었다.

Keywords

References

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