[gdal-dev] downsampling geotiff with a low-pass filter

[jratike80]

Hi,

If a low-pass filter is needed before passing data to downsampling, I wonder
if it could be done by utilizing a VRT with KernelFilteredSource
https://www.gdal.org/gdal_vrttut.html. May well be that it is not relevant
at all, my understanding of mathematics coming from agricultural background.

-Jukka Rahkonen-




kfj wrote
> On 16.11.18 10:07, Even Rouault wrote:
>>> Upsampling is well
>>> covered: cubicspline and lanczos are reasonably sophisticated upsampling
>>> filters,
>> 
>> Did you actually try them for downsampling ? They are for sure widely
>> used in
>> that case already, for example when using gdaladdo to create overviews.
>> For
>> example cubicspline has a filter radius of 2. If you downsample by a
>> factor of
>> X, the effective radius will be 2 X.
> 
> I did try them, and the result looks 'okay', but I have reservations. I 
> come from a DSP background. If my understanding of the mathematics 
> involved is correct, evaluating a spline over a data set will produce 
> values which are appropriate at a given resolution. If you use these 
> values at a lower resolution, you may get aliasing if the initial signal 
> has high frequency content. Aliasing always happens if there is high 
> frequency content and you resample with a lower sampling rate. You can 
> only avoid it by using a low-pass filter before resampling. So I'm 
> trying to find out if this does happen here.
> 
> If I understand this correctly, the effective radius signifies the 
> number of spline coefficients contributing to the interpolated value, it 
> does not imply a low-pass filter. If the spline (and I suspect it's a 
> B-spline) is created by first prefiltering the data and then evaluating 
> the spline at the desired target locations, the interpolation criterion 
> is fulfilled and there is no smoothing.
> 
> Omitting the prefiltering and using the original data as spline 
> coefficients does some smoothing, but from a cubic spline the effect is 
> small and does not vary with the scale of the downsampling, so it would 
> not work equally well for different scale changes.
> 
> Maybe you can point me to the place in the source code where the 
> relevant math happens? I had a look but it's very complex and I did not 
> find my way in easily.
> 
>  > They are for sure widely used
> 
> This doesn't automatically make them correct. If my suspicions are 
> founded, then there may be room for improvement.
> 
> Kay
> 
> 
> 
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