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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
FAST OCCLUSION AND SHADOW DETECTION FOR HIGH RES OLUTION REMOTE SENSING IMAGE
COMBINED WITH LIDAR POINT CLOUD
Xiangyun Hu * *, Xiaokai Li*
? School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road,
Wuhan, CHINA, 430079
Commission VIL, WG VII/6
KEY WORDS : Fast, Occlusion, Shadow, High Resolution, Remote Sensing, LiDAR
ABSTRACT:
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 cons idering 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. M odern graphics processing unit (GPU) is much more powerful
than central processing unit (CPU). We introduce this technology to sp eed 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.
1. INTRODUCTION
The orthophoto is an important component of geographic
information system (GIS) database and has been applied in
many fields. That it has uniform scale and no relief displacement
enables the users to measure distances and areas directly.
However, the traditional generation of orthophotos is based on
digital elevation models (DEM) which doesn't take the buildings
and any other objects above the terrain into account. Occlusion
and shadow effects caused by the abrupt change of surface
height are major aspects of information degeneration in
orthophotos (Rau et al, 2002). In true orthophotos, the
occlusion and shadow should be detected and compensated.
Light Detection and Ranging (LiDAR) integrates the Global
Navigation Satellite System (GNSS) and Inertial Navigation
System (INS) with laser scanning and ranging technologies. It
offers a directly method to measure the three-dimensional
coordinates of points on ground objects and makes the creation
of digital surface models (DSM) very efficient (Disa ef al., 201 1).
Combined with this technology, image occlusion and shadow
can be detected automatically.
The Z-Buffer algorithm is one of the most popular methods
of occlusion detection (Liang-Chen ef al., 2007, Bang ef al,
2007). It calculates the distances between the projection centre
and object points. The closest object point is visible while
others are occluded in one line of sight (Ambar ef al., 1998). The
shadow detection can be regarded as a same problem with
occlusion detection considering the angle between the sun and
the camera (Rau ef al, 2002). However, this method is
computationally intensive (Kato et al., 2010). On the other hand,
*huxy @whu.edu.cn; phone 86 27 687-78010; fax 86 27 687-78086
399
the resolution of the remote sensing images and LiDAR point
cloud is becoming higher and higher, making the large volume of
data in remote sensing greater. It has been one of the main
challenges in data processing.
With the rapid development of computer hardware, the
processing power is growing. Central Processing Unit (CPU)
has entered the era of multi-core and it shows strong parallel
computing power. And Graphic Processing Unit (GPU) has
evolved into highly parallel, multi-threaded, many-core
processors with tremendous computational horsepower and a
very high memory bandwidth (NVIDIA, 2011). It is much more
powerful than CPU in parallel computing capability. Since the
release of Compute Unified Device Architecture (CUDA), it has
become increasingly convenient and efficient to use GPUs to
speed up applications.
In this paper, the method of occlusion and shadow detection
for high resolution remote sensing image combined with LIDAR
point cloud is discussed and the GPU is introduced to accelerate
the algorithm.
2. OCCLUSION AND SHADOWN DETECTION
Occlusion detection is a problem of visibility analysis (Hablb
et al., 2007). And the Z-Buffer algorithm is the most commonly
used method. In the algorithm, an image matrix called z-buffer is
used to store the distance (Z) between the projection centre and
points in the object surface which correspond to the pixels in
the image. An index matrix is also needed to denote the visibility
of every point. Some points may be projected onto the same
pixel. Calculate the distance and compare it with the existing
