On 06/09/12 15:44, Markus Neteler wrote:
Hi Eric,great work with the i.segment, I just made a test with the NC Landsat sample data: i.segment -w -l group=lsat7_2000 output=testsegment threshold=4 \ method=region_growing similarity=euclidean minsize=20 The result looks already pretty nice without further parameter tuning. It would now be cool to susequently perform a unsupervised classification with, say, i.cluster/i.maxlik in order to group the segments to a certain number of classes. Would that be feasible from the resulting image statistics?
I'm not sure that i.cluster is the right tool here. I think it might be more efficient / easier to actually transform the segments into vectors and fill up the attribute table with a whole series of statistics concerning spectral, shape, context, etc characteristics of these segments.
I guess you could also create a whole series of new bands, one for each of the characteristics mentioned above, in which for each pixel you put the statistic of its segment concering the respective characteristic, and submit that to i.cluster. But somehow that doesn't sound as efficient to me...
Moritz _______________________________________________ grass-dev mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-dev
