I am trying to median-filter time series in time and not in space.
Not sure `r.series.filter` is the right tool.
I skimmed through the manual, the paper and the source code. Yet I am
asking for a confirmation.
Its (odd integer) parameter `winsize=` implies a moving window (of size
winsize^2).
Does this rather filter images, of a time series, in space?
Or does the `winsize` here refer to the length of a moving temporal
window?
Then, there is `r.series.lwr`.
Can I use the tool with `order=0` and `delta=1` (or `order=3` and
`delta=1`)
and perform a moving average filtering in time?
It's not median. Still I'd like to see a filtering in time-only effect.
And, now I recall `r.hants`.
Is there a way to use it for filtering-out only lows and highs (`-l` and
`-h` respectively) pixel-wise in time, without interpolating nor
extrapolating?
Else, I guess there should be a way to build a 'custom' filter using
`t.rast.algebra` using its temporal neighborhood modifier.
It's convenient if one the tools above does already median-filtering in
time-only.
Kind regards, Nikos
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