Hi Agustin,
I have a short python example (not tested) which computes the mean of 2
multispectral images by looping over the number of bands, using the
BandMath application and then concatenates the results. You may want to
adapt it in order to apply it to a list of images.
import otbApplication as otb
def multispectralAdd(im1, im2, nbBands, outputName):
tmpImageName = "/tmp/ma" #prefix for temp files
tmpImages = [] #list to hold the temp images
for band in range(nbBands): #we add band by band
tmpImages.append(tmpImageName+str(band)+".tif")
bm = otb.Registry.CreateApplication("BandMath")
bm.SetParameterStringList("il", [im1, im2])
bm.SetParameterString("out", tmpImages[-1])
bm.SetParameterString("exp",
"(im1b"+str(band)+"+im2b"+str(band)+")/"+str(nbBands))
bm.ExecuteAndWriteOutput()
#and we concatenate all the temp files
concat = otb.Registry.CreateApplication("ConcatenateImages")
concat.SetParameterStringList("il", tmpImages)
concat.SetParameterString("out", outputName)
concat.ExecuteAndWriteOutput()
And maybe my example can be used with the reduce function
http://docs.python.org/2/library/functions.html#reduce
I hope this helps.
Bon Nadal.
Jordi
On Friday, December 20, 2013 3:11:49 PM UTC+1, alobo wrote:
>
> Merci!
>
> I will try, although would prefer a shell or python solution.
> I'm also looking at simplecv, although it seems that reading
> images > 3 bands is not easy.
>
> Have a nice Xmas season!
>
> Agus
>
> On Fri, Dec 20, 2013 at 10:11 AM, Julien Malik
> <[email protected]<javascript:>>
> wrote:
> > 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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