Markus (and others) Answering my question
> Is it usefull to make a raster with textural image features as an > extra input for i.gensigset / i.smap? The i.gensigset / i.smap procedure > is partly based on geometry and therefor on texture as well so what does > a texturemap add? Markus Neteler wrote > It's worth trying. I have done so for orthophoto classification and > it definitely helped: > http://mpa.itc.it/markus/ortho_smap/ > > The texture map(s) add patterns which can stabilize the process > of assigning pixels to classes/can improve the segmentation part > of i.smap as it renders heterogeneous areas to homogeneous > areas. > > Thanks for your tips. The explanation of r.texture in the manual pages has puzzled me, and in fact partly it still does. At first I had the impression r.texture was just a slight modification of r.neighbors, but after reading http://www.eng.tau.ac.il/~michal/mri_segmentation/mri_segmentation.html I discovered that r.texture makes use of several quite advanced algorithms. Now I can, at least partly, depict more or less what it effectively is doing. The problem that I am stil facing, is which textural measure might give the best input for i.smap. Anyway I will give Sum Avarage a try. With my dataset (resolution 0,5 meters and mainly smaller trees and shrubs), I will use a distance value of 2 and, following your example, using two windowsize: a smal one of 3 and a medium one of 9. Untill now I used the Variance measure with distance 1 and windowsize 3. I (not knowing what r.texture realy does) used only one direction as input and the result (r,kappa) was worse than with no textural measure. This was caused by i.e. transitions from water to grassland that (with higher variance) were classified as forest Jonathans bottom-up approach ( http://casil.ucdavis.edu/docman/view.php/52/141/greenbergetal2006b.pdf ) seems interesting. I might give that one a try for a more detailed classification as a testcase, since we have also a detailed vegetation map (scale 1:5000, dating from 2005) at hand that we use for training sites in our coarser classification. Regards, Wout _______________________________________________ grass-user mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-user
