Julien is right,

MeanShift segmentation cannot be streamed, and it will be time consuming. You 
can use the LSMS workflow to get large images processed. There is a recipe in 
CookBook for that :

https://www.orfeo-toolbox.org/CookBook/recipes/improc.html#large-scale-mean-shift-lsms-segmentation

But processing time will still be quite long for this image size.

Regards,

Julien

De : [email protected] [mailto:[email protected]] De la part 
de Julien Radoux
Envoyé : mardi 6 mars 2018 07:43
À : otb-users <[email protected]>
Objet : [otb-users] Re: Processing time issues!? Image size limitation of OTB?

Hello,

for large images, there is a four step process called "Large Scale Mean Shift 
segmentation. You can find a tutorial in here : 
https://www.orfeo-toolbox.org/CookBook/Applications/app_LargeScaleMeanShift.html

Note that mean shift segmentation is very time consuming, so it is difficult to 
accelerate. On the other hand, streaming is usually activated by default in OTB 
filters, but it works best for pixel based or block based analysis, while 
segmentation needs to keep information about the surrounding pixels at an 
undefined distance, so the memory handling is much more complex (if you don't 
want to see tiles).

Le lundi 5 mars 2018 14:01:50 UTC+1, nouha touihri a écrit :

Hello  all!
I'm trying to segment a pléiade image and  my study area is 123 km^2 = 22000 x 
22000 pixels. The segmentation (meanshift) algorithm is taking more than a week 
now and didn't bypasse 28% of the process! I'm using a work station dell e5! on 
the otb cookbook documentation, the image size limitation of OTB is mentioned 
and they said that this limitation can be bypassed thanks to the streaming 
mechanism implemented within OTB’s pipeline (actually ITK’s). does anyone know 
what OTB’s pipeline means ? how to bypassed the processing time problem?

Best,

Nouha,
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