Journal of the Korea Academia-Industrial cooperation Society Vol. 19, No. 11 pp. 568-573, 2018 https://doi.org/10.5762/kais.2018.19.11.568 ISSN 1975-4701 / eissn 2288-4688 엄대용 1, 박준규 2* 1 한국교통대학교토목공학과, 2 서일대학교토목공학과 Improvement of Ortho Image Quality by Unmanned Aerial Vehicle Dae-Yong Um 1, Joon-Kyu Park 2* 1 Department of Civil Engineering, Korea National University of Transportation 2 Department of Civil Engineering, Seoil University 요약무인항공기는유인항공기에비해가격이저렴하고, 운용이용이하기때문에최근공간정보구축, 농업, 어업, 기상관측, 통신, 엔터테인먼트분야등에서광범위하게사용되고있다. 특히, 공간정보구축관련분야에서무인항공기는데이터취득의신속성과경제성때문에많은주목을받고있다. 하지만무인항공기를이용해제작되는정사영상에는건물이나산림부분의왜곡현상이발생하며, 공간정보분야의원활한활용을위해서는이러한문제를해결할필요가있다. 본연구에서는다양한조건에서무인항공기정사영상의왜곡을파악하기위해고정익, 회전익, 수직이착륙형의무인항공기를활용하여건설현장, 도심지역, 산림지역등다양한대상지역을촬영하고, 정사영상을제작하여분석하였다. 연구를통해무인항공기영상의중복도가왜곡현상의가장큰요인이며, 비행고도가높을수록왜곡현상이감소함을알수있었다. 또한왜곡현상의개선을위한 DTM(Digital Terrain Model) 을활용하는원시영상의해상도를낮추어정사영상의왜곡을감소시킬수있는방안을제시하였다. 향후왜곡없는고품질무인항공기성과물은정밀측량분야의무인항공기적용확대에크게기여할것이다. 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, rotary, 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. Keywords : Digital Surface Model, Digital Terrain Model, Distortion, Ortho Iamge, UAV 1. 서론 공간정보구축관련분야에서무인항공기는데이터 취득의신속성과경제성때문에많은주목을받고있으며 [1,2], 우리나라는무인항공기의안정성검증시범사업공역을선정하고관련사업자컨소시엄을구성하는 본논문은 2015년한국연구재단기본연구자지원사업 (NRF-2015R1D1A1A01060007) 의지원을받아연구되었습니다. * Corresponding Author : Joon-Kyu Park(Seoil University) Tel: +82-10-3409-3935 email: surveyp@empas.com Received September 21, 2018 Revised October 7, 2018 Accepted November 2, 2018 Published November 30, 2018 568
등무인항공기를차세대주력산업으로육성하기위한준비를하고있다 [3-5]. 하지만무인항공기를이용해제작되는정사영상에는건물이나산림부분의왜곡현상이발생하며 [6,7], 공간정보분야의원활한활용을위해서는이러한문제를시급히해결할필요가있다. 무인항공기에대한관심증가와다양한활용에도불구하고, 정사영상의건물이나산림왜곡과같은문제점에대한학술적연구는부족한상황이다. 본연구는다양한조건의실험및분석을통해무인항공기정사영상의왜곡현상의원인과해결책을도출함으로써정확도를요구하는공간정보관련분야에무인항공기를이용한측량을원활하게적용할수있도록하며, 왜곡현상개선기술및노하우를확보하고자하였다. 무인항공기정사영상의왜곡현상해결을위해무인항공기에의한영상의취득과자료처리방안에초점을두고, 연구방향을수립하였으며, 다양한조건에서무인항공기를이용한자료취득, 처리및분석을수행하였다. 2. 무인항공촬영 본연구에서는다양한조건에서정사영상의왜곡을파악하기위해고정익, 회전익, 수직이착륙형의무인항공기를활용하여건설현장, 도심지역, 산림지역등다양한대상지역을촬영하였다. 무인항공촬영현황은 Table 1과같다. Table 1. UAV Data Acquisition Status Type Area Characteristic Height Ansan Construction site 100m Rotary 200m Hwacheon Forest area 300m Daejeon Park area 150m Fixed Pyeongtaek Apartment Area 300m Icheon Farmland 150m VTOL Chuncheon Park area 150m 회전익무인항공기는 Phantom4 pro와 Fox6 모델을이용하였으며, 자료처리를위해 GCP 측량을수행하였다. 고정익무인항공기는 UX5 HP를이용하였으며, PPK(Post Processed Kinematic) 방법을적용하였다. VTOL은 FoxyPro 무인항공기를이용하였으며, GCP 측 량을수행하였다. Fig. 1은연구에활용된무인항공기를 나타낸다 [8-10]. (a) Phantom4 Pro (b) Fox6 (c) UX5 HP (d) FoxyPro Fig. 1. UAV 무인항공촬영을위해미션플래닝소프트웨어를이용 하여비행계획을설정하였으며, Table 2는기체별비행 계획에대한설정값을나타낸다. Table 2. Settings for Flight Planning Model Focal length Overlap Sidelap Pahntom4 Pro 8.65mm 80% 80% 70% 60% Fox6 16mm 80% 70% UX5 HP 15mm 80% 80% FoxyPro 16mm 80% 70% 3. 자료처리및결과분석회전익및수직이착륙형무인항공기로촬영된영상의자료처리는 UAS Master를이용하였으며, 고정익으로촬영된영상은 TBC(Trimble Business Center) 로처리하였다. 자료처리는프로젝트설정, tie point 추출, GCP 관측, orientation, Surface and Ortho Generation의과정으로수행되었다. 각대상지별영상자료처리현황은 Table 3과같으며, Fig. 2는자료처리과정을나타낸다. 569
한국산학기술학회논문지제 19 권제 11 호, 2018 Table 3. Status of Operationg Mine Type Area Post Processing GSD Ansan UAS master 3cm Rotary 4cm Hwacheon UAS master 6cm Daejeon UAS master 5cm Fixed Pyeongtaek TBC 10cm Icheon TBC 6cm VTOL Chuncheon UAS master 3cm Fig. 2. Data Processing (e) Ortho Generation 자료처리를통해연구대상지의정사영상을생성하였으며, 정사영상에대한품질을분석하여왜곡현상에대한특징을파악하였다. Fig. 3은정사영상을나타낸다. (a) Data Import (a) Ansan (b) Hwacheon (b) Tie Point Extraction (c) Daejeon (d) Pyeongtaek (c) GCP Measurement (d) Surface Generation (e) Icheon Fig. 3. UAV Ortho Images (f) Chuncheon 570
무인항공기정사영상의왜곡현상은주로건물, 산림지역과영상의외곽부분에서나타났다. 건물및영상의외곽에서나타난왜곡현상을 Fig. 4와 Fig. 5에나타내었다. Fig. 4에서와같이건물에서발생하는왜곡현상은지형및지물의고도가급격하게변하여중복촬영된연속된영상에서시차가크게발생하는경우발생하는것으로판단된다. 또한영상외곽에서발생하는왜곡현상은촬영지역의중심부에비해중복도가낮기때문인것으로판단된다. 대상지역별왜곡현상현황은 Table 4와같다. Table 4. Distortion Status Type Area Distortion Rotary Fixed Ansan Hwacheon Daejeon Pyeongtaek Icheon Outskirts, Building Outskirts Outskirts, Shadow, Car Tall Building Building, Car, Tree Fig. 4. Image Distortions in Buildings VTOL Chuncheon Outskirts, Building, Road 데이터취득및자료처리결과로부터영상의왜곡및자료처리결과에영향을주는가장큰요인은중복도임을알수있었다. 따라서무인항공기정사영상제작을위한촬영계획설정시중복도를충분히설정해야할것이다. 4. 왜곡현상감소방안 본연구에서는정사영상의왜곡현상을감소시키기위한방안으로 DTM을활용하는방법과 GSD(Ground Sample Distance) 를조정하는방법을적용하였다. DTM 을활용하는경우는지형모델의생성단계에서왜곡현상이일어나지않도록지형을평활화하는방법으로 DSM 생성시지형및지물의고도차로인한일그러짐을없애는것이다. Fig. 6은 DSM과 DTM이며, Fig. 7은 DTM 을이용해영상의왜곡을감소시킨예를나타낸다. Fig. 5. Distortion in the Outline of the Image 571
한국산학기술학회논문지제 19 권제 11 호, 2018 의 1.5배정도 GSD로정사영상을생성하면왜곡현상이일부개선됨을확인하였다. Fig.8은해상도를조정하여영상의왜곡을감소시킨예를나타낸다. (a) DSM (a) Before Fig. 6. DSM and DTM (b) DTM (a) Before (b) After Fig. 8. Reduce Image Distortion by Adjusting Resolution 5. 결론 (b) After Fig. 7. Reduce Image Distortion using DTM GSD를조정하는방법은원영상의해상도보다정사영상의해상도를낮게하는방법으로원시영상의해상도 본연구는다양한조건의실험및분석을통해무인항공기정사영상의왜곡현상의원인과해결책을도출하고자한것으로연구를통해다음과같은결론을얻을수있었다. 1. 무인항공기정사영상의왜곡현상은건물및산림지역과영상의외곽에서주로발생하였으며, 왜곡현상의가장큰원인은촬영된영상의중복도인것으로판단된다. 2. 왜곡현상개선을위한후처리방법으로 DTM을활 572
용하는방법과정사영상의해상도를조정하는방법을제시하였다. 3. 연구결과는무인항공기를활용한촬영및성과산출에서왜곡현상을감소시킬수있는가이드라인으로왜곡없는고품질무인항공기성과물은정밀측량분야의무인항공기적용확대에크게기여할것이다. 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] Dà-Jiāng 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] HÉLICÉO - Geomatic Innovation &Technology, Products, [Internet]. HÉLICÉO, Available From: http://www.heliceo.com/en/ (accessed Oct., 2, 2018) 엄대용 (Dae-Yong Um) [ 정회원 ] < 관심분야 > 지형공간정보공학, 사진측량학 1997 년 2 월 : 충남대학교공과대학토목공학과 ( 공학사 ) 1999 년 2 월 : 충남대학교대학원토목공학과 ( 공학석사 ) 2004 년 2 월 : 충남대학교대학원토목공학과 ( 공학박사 ) 2004 년 4 월 ~ 현재 : 한국교통대학교토목공학과교수 박준규 (Joon-Kyu Park) [ 종신회원 ] < 관심분야 > 지형공간정보공학 2001 년 2 월 : 충남대학교공과대학토목공학과 ( 공학사 ) 2003 년 2 월 : 충남대학교대학원토목공학과 ( 공학석사 ) 2008 년 8 월 : 충남대학교대학원토목공학과 ( 공학박사 ) 2011 년 3 월 ~ 현재 : 서일대학교토목공학과부교수 573