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Extraction of 3D Building Information by Modified Volumetric Shadow Analysis Using High Resolution Panchromatic and Multi-spectral Images

고해상도 전정색 영상과 다중분광 영상을 활용한 그림자 분석기반의 3차원 건물 정보 추출

  • Lee, Taeyoon (Satellite Information Research Center, Korea Aerospace Research Institute) ;
  • Kim, Youn-Soo (Satellite Information Research Center, Korea Aerospace Research Institute) ;
  • Kim, Taejung (Department of Geoinformatic Engineering, Inha University)
  • 이태윤 (한국항공우주연구원 위성정보연구센터) ;
  • 김윤수 (한국항공우주연구원 위성정보연구센터) ;
  • 김태정 (인하대학교 지리정보공학과)
  • Received : 2013.09.03
  • Accepted : 2013.10.17
  • Published : 2013.10.31

Abstract

This article presents a new method for semi-automatic extraction of building information (height, shape, and footprint location) from monoscopic urban scenes. The proposed method is to expand Semi-automatic Volumetric Shadow Analysis (SVSA), which can handle occluded building footprints or shadows semi-automatically. SVSA can extract wrong building information from a single high resolution satellite image because SVSA is influenced by extracted shadow area, image noise and objects around a building. The proposed method can reduce the disadvantage of SVSA by using multi-spectral images. The proposed method applies SVSA to panchromatic and multi-spectral images. Results of SVSA are used as parameters of a cost function. A building height with maximum value of the cost function is determined as actual building height. For performance evaluation, building heights extracted by SVSA and the proposed method from Kompsat-2 images were compared with reference heights extracted from stereo IKONOS. The result of performance evaluation shows the proposed method is a more accurate and stable method than SVSA.

각종 센서 정보에 기반한 3차원 건물 정보 추출 방법은 건물 형태를 보다 상세하게 묘사할 수 있지만 많은 비용 및 복잡한 처리가 요구된다. 단일 고해상도 영상에 기반한 방법은 추출할 수 있는 3차원 건물 정보가 비교적 제한적이지만 낮은 비용과 단순한 처리 과정으로 건물 정보를 추출할 수 있다는 장점을 갖는다. 단일 고해상도 위성영상만을 이용한 건물 정보 추출 방법 중에서도 Volumetric Shadow Analysis(VSA)는 그림자나 건물 밑 바닥이 일부분 가려져도 해당 건물의 높이와 바닥 위치 정보를 추출할 수 있다. 최근에는 반자동 VSA가 제안되었으나 이 방법은 주변 객체 형태와 그림자 영역 추출 정확도, 영상 노이즈 등에 큰 영향을 받는다. 반자동 VSA를 개선하기 위해서 본 논문은 단일 고해상도 전정색 영상과 다중분광 영상을 이용한 3차원 건물 정보 추출 방법을 제안한다. 제안된 방법은 각 밴드 영상에 반자동 VSA를 각각 적용하고 이를 통해서 계산된 파라미터로 비용함수를 구성한다. 비용함수로 계산된 값이 최대인 건물 높이를 실제 건물 높이로 결정한다. 제안된 방법의 성능평가를 위해서 Kompsat-2 영상이 사용되었으며 반자동 VSA와 제안된 방법으로 추출된 건물 정보를 비교 분석하였다. 그 결과는 제안된 방법이 보다 높은 성공률로 비교적 정확한 건물 정보를 추출할 수 있음을 보여준다.

Keywords

References

  1. Aytekin, O., I. Ulusoy, A. Erener, and H. S. B. Duzgun, 2009. Automatic and unsupervised building extraction in complex urban environments from multi spectral satellite imagery, Proc. of Recent Advances in Space Technologies, 2009 4th International Conference on, Jun. 11-13, pp. 287-291.
  2. Baillard, C. and H. Maitre, 1999. 3-D reconstruction of urban scenes from aerial stereo imagery: A focusing strategy, Computer Vision and Image Understanding, 76: 244-258. https://doi.org/10.1006/cviu.1999.0793
  3. Cheng, L., J. Gong, M. Li, and Y. Liu, 2011. 3D building model reconstruction from multi-view aerial imagery and lidar data, Photogrammetric Engineering and Remote Sensing, 77: 125-139. https://doi.org/10.14358/PERS.77.2.125
  4. Fradkin, M., H. Maitre, and M. Roux, 2001. Building detection from multiple aerial images in dense urban areas, Computer Vision and Image Understanding, 82: 181-207. https://doi.org/10.1006/cviu.2001.0917
  5. Huang, H., C. Brenner, and M. Sester, 2013. A generative statistical approach to automatic 3D building roof reconstruction from laser scanning data, ISPRS Journal of Photogrammetry and Remote Sensing, 79: 29-43. https://doi.org/10.1016/j.isprsjprs.2013.02.004
  6. Javzandulam, T.A., T. Kim, and K.O. Kim, 2007. A semi-automated method to extract 3D building structure, Korean Journal of Remote Sensing, 23(3): 211-219. https://doi.org/10.7780/kjrs.2007.23.3.211
  7. Kim, H.J., D.Y. Han, and Y.I. Kim, 2006. Building height extraction using triangular vector structure from a single high resolution satellite image, Korean Journal of Remote Sensing, 22(6): 621-626 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2006.22.6.621
  8. Kim, T. and J.P. Muller, 1998. A technique for 3D building reconstruction, Photogrammetric Engineering and Remote Sensing, 64: 923-930.
  9. Korea Aerospace Research Institute, 2008. Kompsat-2 image data manual, http://earth.esa.int/pub/ESA_DOC/
  10. Lee D.C., J.H. Yom, S.W. Shin, J. Oh, and K. Park, 2011. Automatic building reconstruction with satellite images and digital maps, ETRI Journal, 33(4): 537-546. https://doi.org/10.4218/etrij.11.1610.0020
  11. Lee, T. and T. Kim, 2009. A study on the reproduction of 3-dimensional building model from single high resolution image without meta information, Journal of the Korean Society for GeoSpatial Information System, 17(3): 71-79 (in Korean with English abstract).
  12. Lee, T. and T. Kim, 2013. Automatic building height extraction by volumetric shadow analysis of monoscopic imagery, International Journal of Remote Sensing, 34(16): 5834-5850. https://doi.org/10.1080/01431161.2013.796434
  13. Lee, T.Y., T.J. Kim, and Y.J. Lim, 2006. Extraction of 3D building information using shadow analysis from single high resolution satellite images, Journal of the Korean Society for GeoSpatial Information System, 14(2): 3-13 (in Korean with English abstract).
  14. Lin, C. and R. Nevata, 1998. Building detection and description from a single intensity image, Computer Vision and Image Understanding, 72:101-121. https://doi.org/10.1006/cviu.1998.0724
  15. Liow, Y.T. and T. Pavlidis, 1990. Use of shadows for extracting building in aerial images, Computer Vision, Graphics and Image Processing, 49:242-277. https://doi.org/10.1016/0734-189X(90)90139-M
  16. Radhadevi, P.V., S.S. Solanki, M.V. Jyothi, V. Nagasubramanian, and G. Varadan, 2009. Automated co-registration of images from multiple bands of Liss-4 camera, ISPRS Journal of Photogrammetry and Remote Sensing, 64(1):17-26. https://doi.org/10.1016/j.isprsjprs.2008.06.003
  17. Rau, J.Y. and L.C. Chen, 2003. Robust reconstruction of building models from three-dimensional line segments, Photogrammetric Engineering and Remote Sensing, 69: 181-188. https://doi.org/10.14358/PERS.69.2.181
  18. Sohn, G. and I. Dowman, 2007. Data fusion of highresolution satellite imagery and LiDAR data for automatic building extraction, ISPRS Journal of Photogrammetry and Remote Sensing, 62: 43-63. https://doi.org/10.1016/j.isprsjprs.2007.01.001
  19. Sohn, H.G., C.H. Park, and J. Heo, 2005. 3-D building reconstruction using IKONOS multispectral stereo images, Lecture Notes in Computer Science, 3683: 62-68. https://doi.org/10.1007/11553939_9
  20. Vu, T.T., F. Yamazaki, and M. Matsuoka, 2009. Multiscale solution for building extraction from LiDAR and image data, International Journal of Applied Earth Observation and Geoinformation, 11: 281-289. https://doi.org/10.1016/j.jag.2009.03.005

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