In: Wagner W., Szekely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
while the RMSE of Sample 53 is worse than DDASF. Generally 
speaking, DDASF is much stable than the other two methods 
based on the results of classification accuracy and RMSE. 
(b) classification accuracy on Sample 53 
works, a variety of terrain features need to be tested to ensure 
the reliability of DDASF. 
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(c) RMSE on Sample 23 and Sample 53 
Figure 11. Classification accuracy and RMSE on both data 
4. CONCLUSION AND SUGGESTION 
This paper proposes a modified slope-based filter, DDASF, 
with an additional consideration of filter directions. The 
experimental results show that DDASF can improve the over- 
filtering situation over the discontinued areas and improve 
DEM quality over other areas compared with the other two 
filters. For classification accuracy, DDASF behaves more 
stably. Since the points near the cliff areas can be retained, both 
of classification errors and RMSE values decrease. For future