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image and the result of shadow detection. All experiments are
done on a PC with Intel(R) Core(TM) i7-920 @ 2.67 Hz CPU
with 4.0 GB memory, a NVIDIA GeForce GTX285 GPU with
1.0 GB memory, and Windows 7 Ultimate - 64bit system.
Using Z-Buffer to detect the occlusion takes about 24.2 seconds
in CPU. The implementation in OpenGL needs about 4.3s.
Accelerated by CUDA in GPU, the time is less than 3.4s and
we get over 7 times’ speedup. It is noteworthy that the creation
of TIN takes about 2.1s. So the limit of the running time is not
the calculation of the z-buffer any more.
cluded Area [8 2
(c)
Figure 4. Occlusion Detection
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
®)
Figure 5. Shadow Detection
5. CONCLUSION
In this paper, the Z-Buffer algorithm is used to detect the
occlusion and the shadow whose detection and compensation is
a critical step in the generation of true orthophoto. GPU is
introduced to accelerate the process. Experimental results
indicate that the fast detection of occlusion and shadow
combined with LIDAR point cloud is effective and efficient.
There are still some key point of the algorithm needs to be
studied further. Firstly, the precision of the detection result
need to be improved. In this paper, only coarse edges are
obtained. Secondly, the compensation of the occlusion and
shadow using multi-view images is another problem. Thirdly,
only NVIDIA’s GPUs support CUDA. Open Computing
Language (OpenCL) is a better alternative. These three aspects
are the direction of our future research.
6. ACKNOWLEDGEMENTS
Thank Guangzhou Jiantong Surveying and Mapping
Technology Development Ltd. for providing the experimental
data.
REFERENCE
Ambar F., Jansa J. and Ries C., 1998. The generation of true
orthophotos using a 3D building model in conjunction with a
conventional DTM. International Archives of Photogrammetry
and Remote Sensing, 32(4): 16-22.
Bang KI. and Habib A.F., 2007. Comparative analysis of
alternative methodologies for true ortho-photo generation from
high resolution satellite imagery. ASPRS 2007 Annual
Conference.
Chen L.C., Teo T.A., Wen J.Y., Rau J.Y., 2007. Occlusion-
Compensated True Orthorectification for High-Resolution
Satellite Images. The Photogrammetric Record, 22(117), pp. 39-
52.
Disa N.M., Maarof I., Latif Z.A. and Samad A.M., 2011.
LiDAR: A Review On Generating Digital True Orthophoto.
IEEE 7th International Colloquium on Signal Processing and its
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