Full text: Close-range imaging, long-range vision

167 points 
Figure 2. Test site 
878 points 
Figure 3. Intensity image 
3.1 Noise Reduction 
In the case of ground based laser scanning, many noises which 
were caused by trees are estimated, and these noises have to 
remove by automatically. Hence, automatic noise reduction 
method was investigated. 
Detail procedures for noise reduction are as follows, and Figure 
4 shows the flow of automatic noise reduction method, and 
Figure 5 shows position of topographic and noise data. 
Three procedures were investigated as noise reduction methods, 
the first is noise reduction by Z values, the second is performed 
using distance between neighboring points, and intensity image 
was used at the final step. 
eNoise Reduction by Z values. 
+ Search a point which have smaller Z values and have similar 
XY values compare with an interest point in neighboring an 
interest point. 
+ If detect such a point, an interest point is removed as a noise. 
+ If an interest point has the minimum Z values, an interest 
point is identified as a ground. 
Repeating the above procedures, noises which caused by trees 
were considerably removed. 
However, there are still some noises in mass area of trees. In 
order resolve the second issue, the following procedures were 
+ Select an interest point in the mass area using intensity image. 
+ Calculate distances between an interest point and neighboring 
+ If there are many shorter distances, an interest point is 
identified as a ground. 
+ If there are many longer distance, an interest point is reduced 
as a noise. 
As the final step, a few noises were reduced as a labeling 
procedure using intensity image. 
| Pick a Interes Point 
No d = 
——— Same XY Value 
S qe e 
y Yes 
< Smaller Z Values? 
Sma u 
»—  Shoter Distances? 7 
M uu 
S es . 
y Yes | Noise | 
| Topographic Data | 
a er ed 
Figure 4. Flow of automatic noise reduction 
Z3 Noise data 
c — pem m ee 
—»| Topographic data 
Figure 5. Position of topographic and noise data 

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