Hi Agus,

I don't see a straight forward way to do this with otb_cli or otb-python
(there might be one), but this is a very easy one if you are not afraid
of writing a bit a C++.
I would do it like this :
- build up a VRT concatenating all the images with GDAL.
- write a very simple pipeline Reader->MatrixImageFilter->Writer.
- building up your transformation accordingly. N being you number of
images, this would be a 6N x N matrix filled with (1/N) at the right places.

Actually the code you need is already written in a test :
http://hg.orfeo-toolbox.org/OTB/file/6211d0ccba0f/Testing/Code/BasicFilters/otbMatrixImageFilterTest.cxx#l40
You just have to adapt the matrix size and filling.

It would be multithreaded and streamed.
This would give you very decent performances I think.

You can follow this :
http://www.orfeo-toolbox.org/SoftwareGuide/SoftwareGuidech2.html#x14-330002.3
for instructions on how to build the CMakeLists that will compile your
project.

Cheers,
Julien


On 12/19/2013 01:14 PM, Agustin Lobo wrote:
> I have to calculate the average multi-spectral image (6 bands)
> over a set of ~100 images (6x1024x1280). That is, having 3 multiespectal
> images A,B and C, I need M in which band1 is the average band1 of A, B and C
> and so on. Also, I first subtract the mean for each band.
>
> I currently do this in R, but takes a very long time. I essentially
> make an stack (which is like a vrt file) with all bands and then
> calculate the average of bands 1,7,13...
> 2,8, 14... etc
> Is there a way of making this
> calculation using either otb_cli or python-otb ?
>
> Thanks
>
> Agus
>

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