FAST OCCLUSION AND SHADOW DETECTION FOR HIGH RESOLUTION REMOTE SENSING IMAGE COMBINED WITH LIDAR POINT CLOUD

Article, Other literature type English OPEN
Hu, X. ; Li, X. (2012)
  • Publisher: Copernicus Publications
  • Journal: (issn: 2194-9034, eissn: 2194-9034)
  • Related identifiers: doi: 10.5194/isprsarchives-XXXIX-B7-399-2012
  • Subject: TA1-2040 | T | TA1501-1820 | Applied optics. Photonics | Engineering (General). Civil engineering (General) | Technology
    acm: ComputingMethodologies_COMPUTERGRAPHICS | ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION | GeneralLiterature_MISCELLANEOUS

The orthophoto is an important component of GIS database and has been applied in many fields. But occlusion and shadow causes the loss of feature information which has a great effect on the quality of images. One of the critical steps in true orthophoto generation is the detection of occlusion and shadow. Nowadays LiDAR can obtain the digital surface model (DSM) directly. Combined with this technology, image occlusion and shadow can be detected automatically. In this paper, the Z-Buffer is applied for occlusion detection. The shadow detection can be regarded as a same problem with occlusion detection considering the angle between the sun and the camera. However, the Z-Buffer algorithm is computationally expensive. And the volume of scanned data and remote sensing images is very large. Efficient algorithm is another challenge. Modern graphics processing unit (GPU) is much more powerful than central processing unit (CPU). We introduce this technology to speed up the Z-Buffer algorithm and get 7 times increase in speed compared with CPU. The results of experiments demonstrate that Z-Buffer algorithm plays well in occlusion and shadow detection combined with high density of point cloud and GPU can speed up the computation significantly.
  • References (8)

    Hablb A.F., Klm E.M . and Klm C.J., 2007. New methodologies for true orthophoto generation. Photogrammetric Engineering & Remote Sensing, 73(1), pp.025-036.

    Kato A., M oskal L.M ., Schiess P., Calhoun D. and Swanson M .E., 2010. True orthophoto creation through fusion of LiDAR derived digital surface model and aerial photos. International Archives of Photogrammetry and Remote Sensing, 38(7A): 88- 93.

    NVIDIA CUDATM, 2011. NVIDIA CUDA C Programming Guide. NVIDIA, pp.1-1.

    Segal M . and Akeley K., 2012. The OpenGL Graphics System: A Specification.

    Qin Z., Li W., Li M ., Chen Z. and Zhou G., 2003. A methodology for true orhtorectification of large-scale urban aerial images and automatic detection of building occlusions using digital surface model. IEEE International Geoscience and Remote Sensing Symposium, 2, pp.729-731.

    Rau J.Y., Chen N.Y., Chen L.C., 2002. True Orthophoto Generation of Built-Up Areas Using M ulti-View Images.

    Photogrammetric Engineering & Remote Sensing, 68(6), pp.581-588.

    Zhou G., Chen W., Kelmelis J.A. and Zhang D., 2005. A Comprehensive Study on Urban True Orthorectification. IEEE Transaction on Geoscience and Remote Sensing, 43(9), pp.

  • Metrics
    No metrics available
Share - Bookmark