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
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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@manchester.ac.uk