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

  • 제40권3호
  • /
  • Pages.217-226
  • /
  • 2022
  • /
  • 1598-4850(pISSN)
  • /
  • 2288-260X(eISSN)
한국측량학회 (Korean Society of Surveying, Geodesy, Photogrammetry and Cartography)
권호 표지
DOI QR코드

DOI QR Code

Siemens star를 이용한 드론 영상의 품질 평가

Quality Evaluation of Drone Image using Siemens star

  • Lee, Jae One (Dept. of Civil Engineering, Dong-A University) ;
  • Sung, Sang Min (CCZ Forest Management Office, Korea Forest Conservation Association) ;
  • Back, Ki Suk (School of Building & Environment Design, Ulsan College) ;
  • Yun, Bu Yeol (Dept. of Real Estate, Chang-Shin University)
  • 투고 : 2022.06.08
  • 심사 : 2022.06.15
  • 발행 : 2022.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

고정밀 공간정보제작 분야의 활용 측면에서 무인항공사진측량은 촬영된 영상의 정량적인 품질 검증 방법과 인증에 대한 절차와 세부 규정이 미흡한 문제점이 있다. 또한, 영상에 대한 검증 수단이 해상도와 명암의 대비 정도를 동시에 분석 할 수 있는 MTF (Modulation Transfer Function) 분석이 아닌 GSD (Ground Sample Distance) 만으로 품질을 평가하고 있어 유인항공영상보다 품질이 떨어지는 경우도 있다. 이에 본 연구에서는 드론 영상 품질 분석에서 MTF 분석의 필요성을 확인하기 위해 Siemens star를 이용하여 GSD와 MTF 분석을 동시에 실시하였다. 서로 다른 드론 기체와 센서로 동일한 해상도로 타겟을 촬영한 영상을 분석한 결과, GSD에서는 약간 상이한 결과를 나타내었지만, 영상의 해상도와 명암의 대비 정도를 동시에 분석할 수 있는 σMTF 수치는 큰 차이를 나타내었다. 이와 같은 결과로 MTF 분석이 보다 객관적이며 신뢰도 높은 품질분석 방법이라고 결론지을 수 있다. 아울러 작업자가 카메라 센서의 성능, 중복도 및 기체의 성능을 적절하게 판단하여 촬영을 실시하여야만 높은 품질의 드론 영상을 획득할 수 있음을 알 수 있었다. 하지만 본 연구는 제한된 기체와 촬영 조건하에서 취득된 영상으로만 분석을 수행한 결과이다. 따라서 향후 관련 분야의 다양한 실험 데이터를 축척하여 지속적인 연구를 수행하면 보다 객관적이고 신뢰성 있는 결과를 도출할 것으로 기대된다

In the view of the application of high-precision spatial information production, UAV (Umanned Aerial Vehicle)-Photogrammetry has a problem in that it lacks specific procedures and detailed regulations for quantitative quality verification methods or certification of captured images. In addition, test tools for UAV image quality assessment use only the GSD (Ground Sample Distance), not MTF (Modulation Transfer Function), which reflects image resolution and contrast at the same time. This fact makes often the quality of UAV image inferior to that of manned aerial image. We performed MTF and GSD analysis simultaneously using a siemens star to confirm the necessity of MTF analysis in UAV image quality assessment. The analyzing results of UAV images taken with different payload and sensors show that there is a big difference in σMTF values, representing image resolution and the degree of contrast, but slightly different in GSD. It concluded that the MTF analysis is a more objective and reliable analysis method than just the GSD analysis method, and high-quality drone images can only be obtained when the operator make images after judging the proper selection the sensor performance, image overlaps, and payload type. However, the results of this study are derived from analyzing only images acquired by limited sensors and imaging conditions. It is therefore expected that more objective and reliable results will be obtained if continuous research is conducted by accumulating various experimental data in related fields in the future.

키워드

과제정보

이 논문은 교신저자 성상민의 박사학위논문을 바탕으로 작성되었습니다.

참고문헌

  1. Agisoft, (2020), Metashape user manual: Professional edition, ver 1.5.
  2. Dabrowski, R. and Jenerowicz, A. (2015), Preliminary results form the portable image quality assessment test field(PIQuAT) of UAV imagery for imagery reconnaissance purposes, ISPRS Workshop, 30 August-02 September, 2015, Toronto, Canada, pp.111-115. https://doi.org/10.5194/isprsarchives-xl-1-w4-111-2015
  3. Jiang, W., Li, Y., Liang, Y., and Zeng, Y. (2010), Research on quality index system of digital aerial photography results, 4th Computer and Computing Technologies in Agriculture, CCTA, Oct 2010, Nanchang, China, pp. 381-391. https://doi.org/10.1007/978-3-642-18336-2_47
  4. Lee, J.O. and Sung, S.M. (2019), Quality evaluation of UAV images using resolution target, Journal of the Korean Association of Geographic Information Studies, Vol.22 No.1, pp.103-113. (in Korean with English abstract) https://doi.org/10.11108/KAGIS.2019.22.1.103
  5. Lee, J.O. and Sung, S.M. (2020), Edge Response Analysis of UAV-Images Using a Slanted Target, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography, Vol.38 No.4, pp.317-325. (in Korean with English abstract) https://doi.org/10.7848/ksgpc.2020.38.4.317
  6. Lee, T.Y. (2012), Spatial Resolution Analysis of Aerial Digital Camera, Ph.D. dissertation, Dong-A University, Busan, Korea, 50p. (in Korean with English abstract)
  7. Lim, P.C., Seo, J.H., and Kim, T.J. (2018), Extraction of UAV image sharpness index using edge target analysis, Korean Journal of Remote Sensing, Vol.34, No.6-1, pp.905-923. (in Korean with English abstract) https://doi.org/10.7780/kjrs.2018.34.6.1.6
  8. Liang, Y., Zeng, Y., Jiang, W., and Wang, X. (2011), Research on automatic inspection methods of image quality of digital aerial photography results, 5th Computer and Computing Technologies in Agriculture, CCTA, Oct 2011, Beijing, China, pp. 320-331. https://doi.org/10.1007/978-3-642-27275-2_37
  9. Lord Rayleigh, F.R.S. (1879), Investigations in Optics, with Special Reference to the Spectroscope. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science Series 5, 8, 261-274. https://doi.org/10.1080/14786447908639684
  10. National Geographic Information Institute, Airborne photogrammetry Operation Regulations, Suwon. pp.55, 2016.
  11. Neumann, A., (2003), Verfahren zur Auflosungsmessung Digitaler Kameras, Diplomarbeit, University of Applied Sciences Cologne, Cologne, Germany, 70p.
  12. Sandau, R., (2010), Digital Airborne Camera, Introduction and Technology, Springer, Heidelberg.
  13. Sieberth, T., Wackrow, R., and Chandler, J. (2016), Automatic detection of blurred images in UAV image sets, ISPRS Journal of Photogrammetry and Remote Sensing, Vol 122, pp.1-16. https://doi.org/10.1016/j.isprsjprs.2016.09.010
  14. Sung, S.M. (2019), A Study on Spatial Resolution Analysis Methods of UAV Images, Ph.D.dissertation, Dong-A University, Busan, Korea, 49p. (in Korean with English abstract)