Thank you Vero.
Consider the following time series [1, 2, 2, 6, 3, 3, 4, 4, 3, 2, 2, 1]
<- evolution of a pixel in time.
Say this is always the same pixel indexed at [0, 0] in each of 12 raster
maps registered in a GRASS GIS STRDS.
Median filtering pixel-wise in time, only, with a temporal window=3,
would then be doing:
1st pixel would be replaced by the median of [0, 1, 2]
2nd pixel would be replaced by then median of [1, 2, 2]
3rd pixel would be replaced by the median of [2, 2, 6]
4th pixel would be replaved by the median of [2, 6, 3]
etc.
Doing a spatial median over a 2D (sub)window of each raster map in a
GRASS GIS STRDS is not wanted here. I hope this is more clear now.
Nikos
---
On 2021-01-27 16:04, Veronica Andreo wrote:
What exactly do you mean by median-filtering in time only, Nikos? Get the median and then filtering out all pixels above/below that value? If that's the case, then maybe some of the examples here https://grasswiki.osgeo.org/wiki/Temporal_data_processing#Spatio-temporal_algebra_with_STRDS might be of help
Basically, you first estimate the median of the series (or the period you are interested in) either with r.series or t.rast.series and then use t.rast.mapcalc or t.rast.algebra to get only pixels below/above that value represented pixelwise in the median map. It can also be a single value of course.
Does that make sense?
best,
Vero
El mié., 27 ene. 2021 08:44, <n...@nikosalexandris.net> escribió:
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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