[pdal] tweaking parameters in filters.smrf
Bradley Chambers
brad.chambers at gmail.com
Fri Jun 7 09:29:01 PDT 2019
Karl,
On Fri, Jun 7, 2019 at 12:09 PM Karl North <karln at surdex.com> wrote:
> The main issue that I currently have with my PDAL result is the presence
> of too much high frequency “noise” visible in the surface defined by the
> ground classified points. A lesser issue is the delicate balance, when
> using the cut grid parameter to help eliminate building points, between the
> removal of building features and preserving sufficient terrain detail.
>
The issue you've mentioned with and without cut is well known. It would be
interesting to hear more about what you are seeing with the high frequency
noise though.
> Is there anyone out there on the mailing list that can suggest such
> write-ups, or would be willing to share their insights?
>
I don't know of any write-ups other than the original paper. The original
author also has his MATLAB code on GitHub (
https://github.com/thomaspingel/neilpy), though I don't recall that there
are any hints on what parameters to tweak for specific environments.
> Perhaps there are other (as yet undiscovered) PDAL filters that I might
> include in my pipeline either before or after SMRF that would be better
> suited to the remaining cleanup than tweaking the SMRF parameters
> themselves.
>
One thing that comes to mind, though it would take some experimentation,
would be to run a cluster filter (
https://pdal.io/stages/filters.cluster.html#filters-cluster) after SMRF and
then to filter out clusters that were small. I'd maybe use this without cut
to find those roof segments that got left behind and may end up as their
own clusters.
> I can share sample LAZ data illustrating a SMRF-vs-TSCAN comparison of
> current my state-of-the-art, if this will help clarify the current
> issue(s). To do so, I could use some guidance on reasonable limits on file
> size for sharing such a sample.
>
It would certainly be interesting to see the data. Other users in the past
have posted to Google Drive, Dropbox, or similar.
Brad
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