Le 15/12/2014 10:08, Agustin Lobo a écrit :
Consider the workflow provided in
http://www.orfeo-toolbox.org/CookBook/CookBooksu42.html
1. Which metric is the one being used as "ranger" in otbcli_MeanShiftSmoothing
and otbcli_LSMSSegmentation? is it just a range
of DN to be applied to each single band? is it an euclidean distance
in the space of all bands?
It is a spectral euclidean distance.
2. For otbcli_LSMSSegmentation: how are pixels included in one cluster
in the case of multi-spectral images? The manual sates
"This application will produce a labeled image where neighbor pixels
whose range distance is below range radius (and optionally spatial
distance below spatial radius) will be grouped together into the same
cluster."
but this is unambiguous just in the case of one single band. How is
the multi-band case managed? Are pixels grouped if their range
distance is <= ranger for all bands?
Since range distance is euclidean it is a R^n -> R application, so there
is no ambiguity.
4. Are images normalized before the "range distance" is calculated?
No, it is the responsibility of the user to provide an input feature
space where euclidean distance is (at least a bit) meaningful.
Thanks for clarifying these details, they do matter for the user to
select the appropriate ranger parameter.
If you did not already read it, you can read our paper which explains
into details this method :
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6849524&queryText%3DArbitrarily+large+remote+sensing+images
Regards,
Julien
--
Julien MICHEL
CNES - DCT/SI/AP - BPI 1219
18, avenue Edouard Belin
31401 Toulouse Cedex 09 - France
Tel: +33 561 282 894 - Fax: +33 561 283 109
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