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Improvement of Ortho Image Quality by Unmanned Aerial Vehicle

UAV에 의한 정사영상의 품질 개선 방안

  • Um, Dae-Yong (Department of Civil Engineering, Korea National University of Transportation) ;
  • Park, Joon-Kyu (Department of Civil Engineering, Seoil University)
  • 엄대용 (한국교통대학교 토목공학과) ;
  • 박준규 (서일대학교 토목공학과)
  • Received : 2018.09.21
  • Accepted : 2018.11.02
  • Published : 2018.11.30

Abstract

UAV(Unmanned Aerial Vehicle) is widely used in space information construction, agriculture, fisheries, weather observation, communication, and entertainment fields because they are cheaper and easier to operate than manned aircraft. In particular, UAV have attracted much attention due to the speed and cost of data acquisition in the field of spatial information construction. However, ortho image images produced using UAVs are distorted in buildings and forests. It is necessary to solve these problems in order to utilize the geospatial information field. In this study, fixed wing, rotary wing, vertical take off and landing type UAV were used to detect distortions of ortho image of UAV under various conditions, and various object areas such as construction site, urban area, and forest area were captured and analysed. Through the research, it was found that the redundancy of the unmanned aerial vehicle image is the biggest factor of the distortion phenomenon, and the higher the flight altitude, the less the distortion phenomenon. We also proposed a method to reduce distortion of orthoimage by lowering the resolution of original image using DTM (Digital Terrain Model) to improve distortion. Future high-quality unmanned aerial vehicles without distortions will contribute greatly to the application of UAV in the field of precision surveying.

무인항공기는 유인항공기에 비해 가격이 저렴하고, 운용이 용이하기 때문에 최근 공간정보 구축, 농업, 어업, 기상관측, 통신, 엔터테인먼트 분야 등에서 광범위하게 사용되고 있다. 특히, 공간정보 구축 관련 분야에서 무인항공기는 데이터 취득의 신속성과 경제성 때문에 많은 주목을 받고 있다. 하지만 무인항공기를 이용해 제작되는 정사영상에는 건물이나 산림부분의 왜곡현상이 발생하며, 공간정보 분야의 원활한 활용을 위해서는 이러한 문제를 해결할 필요가 있다. 본 연구에서는 다양한 조건에서 무인항공기 정사영상의 왜곡을 파악하기 위해 고정익, 회전익, 수직이착륙형의 무인항공기를 활용하여 건설현장, 도심지역, 산림지역 등 다양한 대상지역을 촬영하고, 정사영상을 제작하여 분석하였다. 연구를 통해 무인항공기 영상의 중복도가 왜곡현상의 가장 큰 요인이며, 비행고도가 높을수록 왜곡현상이 감소함을 알 수 있었다. 또한 왜곡현상의 개선을 위한 DTM(Digital Terrain Model)을 활용하는 원시영상의 해상도를 낮추어 정사영상의 왜곡을 감소시킬 수 있는 방안을 제시하였다. 향후 왜곡 없는 고품질 무인항공기 성과물은 정밀측량분야의 무인항공기 적용 확대에 크게 기여할 것이다.

Keywords

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Fig. 1. UAV

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Fig. 2. Data Processing

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Fig. 4. Image Distortions in Buildings

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Fig. 5. Distortion in the Outline of the Image

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Fig. 6. DSM and DTM

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Fig. 7. Reduce Image Distortion using DTM

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Fig. 8. Reduce Image Distortion by Adjusting Resolution

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Fig. 3. UAV Ortho Images

Table 1. UAV Data Acquisition Status

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Table 2. Settings for Flight Planning

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Table 3. Status of Operationg Mine

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Table 4. Distortion Status

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References

  1. G. H. Kim, J. W. Choi, "Land Cover Classification with High Spatial Resolution Using Orthoimage and DSM Based on Fixed-Wing UAV", Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol.35, No.1, pp. 1-10, February, 2017. DOI: https://doi.org/10.7848/ksgpc.2017.35.1.1
  2. S. C. Lee, J. H. Kim, J. S. Um, "Accuracy and Economic Evaluation for Utilization of National/Public Land Actual Condition Survey Using UAV Images", Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol.35, No.3, pp. 175-186, June, 2017. DOI: https://doi.org/10.7848/ksgpc.2017.35.3.175
  3. J. H. Kim, J. H. Kim, "Accuracy Analysis of Cadastral Control Point and Parcel Boundary Point by Flight Altitude Using UAV", Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol.36, No.4, pp. 223-233, August, 2018. DOI: https://doi.org/10.7848/ksgpc.2018.36.4.223
  4. J. K. Park, K. W. Lee, "Analysis of Geospatial Information about Submergence Area using UAV", International Journal of Software Engineering and Its Applications, Vol.10, No.12, pp. 31-40, December, 2016. DOI: http://dx.doi.org/10.14257/ijseia.2016.10.12.04
  5. K. W. Lee, J. K. Park, "Construction of 3D Digitizing Data Using Aerial Photographs Acquired by UAV", International Journal of Advanced Science and Technology, Vol.112, pp. 79-88, March, 2018. DOI: http://dx.doi.org/10.14257/ijast.2018.112.08
  6. D. I. Kamg, H. G. Moon, S. Y. Sun, J. G. Cha, "Applicability of UAV in Urban Thermal Environment Analysis", Journal of the Korean Institute of Landscape Architecture, Vol.46, No.2, pp. 52-61, April, 2018. DOI: https://doi.org/10.9715/KILA.2018.46.2.052
  7. Y. J. Kim, J. H. Oh, C. N. Lee, "Electric Power Line Dips Measurement Using Drone-based Photogrammetric Techniques", Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol.35, No.6, pp. 453-460, December, 2017. DOI: https://doi.org/10.7848/ksgpc.2017.35.6.453
  8. Da-Jiang Innovations, Phantom4 Pro. [Internet]. DJI, Available From: https://www.dji.com (accessed Jun., 11, 2018)
  9. Trimble Inc., UX5 HP, [Internet]. Trimble Inc. Available From: https://www.trimble.com (accessed Jun., 8, 2018)
  10. HELICEO - Geomatic Innovation &Technology, Products, [Internet]. HELICEO, Available From: http://www.heliceo.com/en/ (accessed Oct., 2, 2018)