[GRASS-user] r.neighbors, wide filtering

[John Stevenson]

Hi,

For my research, I am testing a mesh denoising algorithm on topographic 
data.  It smooths the surfaces much like using r.neighbors 
method=average or r.neighbors method=median, and, depending on 
settings,  gives similar results to r.neighbors when size <5.  The 
advantage of the algorithm is that it has some ability to preserve 
features.  In cases where more significant smoothing is necessary 
(r.neighbors size > 5) it is much better at preserving minimum and 
maximum elevations etc as it converges on a stable solution for the 
smoothed landscape.

My question relates to understanding in which cases is it necessarily to 
smooth to such an extent?  From what I have seen e.g. taking speckle out 
of SRTM DEMs, smoothing by such extremes removes a lot of useful 
information and results in unrealistic surfaces.

Has anyone come across a situation/dataset or type of analysis where 
they need to smooth with r.neighbors (method=average/median, size > 5)?  
I would be interested to know, and to see if this algorithm would be useful.

Cheers

John

-- 


Dr John Stevenson
Postdoctoral Research Associate
School of Earth, Atmospheric and Environmental Sciences
Williamson Building (Room 2.42)
University of Manchester
Manchester M13 9PL, UK
tel. +44(0)161 306 6585; fax. +44(0)161 306 9361;
john.stevenson at manchester.ac.uk