4. CONCLUSION 
All presented methods have a same basics assumption: The 
topographic terrain features are in dimension much larger than 
objects that are filtered out. The off-terrain points are treated as 
a high frequent, but not normally distributed, noise 
superimposed on observed signal. So, the presented methods 
works fine in regions with a clear difference between useful 
signal and "noise" in spatial or frequency domain. Otherwise, in 
regions where this difference is not so obvious (i.e. rocky 
environment"), the result of classification and filtering is not so 
reliable (Kraus and Rieger 1999). Therefore, the other 
information about measured region (i.e. intensity of received 
measuring signal, orthophotos, topographic maps, etc.) and 
objects above them are of most importance. The new 
generations of LIDAR filters are oriented to combine 
geometrical data with intensity data captured by LIDAR and/or 
information from other data sources. 
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