Dear Manuel, Agus I am trying to understand all those parameters in 4 step LSMS. I am sending, what I have found, or what is not clear to me. I will be glad for any comments:
I have found sections of linked paper * "B. Overview of the Algorithm" on page 957 -- filtering step * "D. Proposed Stable Version" on page 958 -- segmentation step * (B. Algorithm for Large-Scale Segmentation" on page 959) most corresponding to 4 steps LSMS procedure described on following pages: http://otbcb.readthedocs.io/en/latest/Applications/app_MeanShiftSmoothing.html http://otbcb.readthedocs.io/en/latest/Applications/app_LSMSSegmentation.html and implemented here https://github.com/orfeotoolbox/OTB/blob/master/Modules/Filtering/Smoothing/include/otbMeanShiftSmoothingImageFilter.txx https://github.com/orfeotoolbox/OTB/blob/master/Modules/Segmentation/MeanShift/include/otbMeanShiftSegmentationFilter.txx What is not clear to me, or some notes: * step 1 -- Filtering step / smoothing (described in "B. Overview of the Algorithm" on page 957) * spatialr (int) -- h_s -- spatial range or spatial kernel bandwidth? -- number of pixels considered during the equation? (seems when set bigger number the computation is slower) * ranger (float) -- h_r -- adjusting the level of smoothing? (with very low value the effect of smoothing not visible) -> resulting Spatial Image -- NOT CLEAR * found * Spatial image output is a displacement map (pixel position after convergence). found here <http://otbcb.readthedocs.io/en/latest/Applications/app_MeanShiftSmoothing.html> * foutpos is actually an image of the spatial position to which each pixel mode converges. found here <https://groups.google.com/forum/#!searchin/otb-users/spatialr|sort:relevance/otb-users/meulMchcxjw/h2LwxVyHgmkJ> * it has 2 bands, it is X and Y distance? * step 2 -- segmentation step * ranger (float) -- h'_r -- seems that this parameter is controlling the number of resulting segments * spatialr (float) -- h'_s Is it possible to somehow control maximum size of segments, or something like spatial compactness? Best regards, Jiří. On Thursday, 3 March 2016 10:12:19 UTC+1, Grizonnet Manuel wrote: > > Hi Augustin, > > the methodology is based on the following publication: > > J. Michel, > D. Youssefi and M. Grizonnet, "Stable Mean-Shift Algorithm and Its > Application > to the Segmentation of Arbitrarily Large Remote Sensing Images," in IEEE > Transactions on Geoscience and Remote Sensing, vol. 53, no. 2, pp. > 952-964, > Feb. 2015. > > You'll find more detail information about the strategy. Note that I've > updated the cookbook recipe sources to add a reference to this > publication which was missing. > > Thanks for the report. > > Manuel > > Le 02/03/2016 10:44, Agustin Lobo a écrit : > > The doc > > https://www.orfeo-toolbox.org/CookBook/CookBooksu35.html#x53-660003.3.4 > > states: > > "The segmentation will group together adjacent pixels whose range > > distance is below the ranger parameter and (optionally) spatial > > distance is below the spatialr parameter" > > > > if the pixels are adjacent, then they always will be below the > > spatialr parameter. Is "adjacency" defined as "within the spatialr > > distance"? > > or is it that the group is allowed to grow at a maximum of spatialr from > the > > considered pixel? > > > > Thanks > > Agus > > > > -- > Manuel GRIZONNET > > -- -- Check the OTB FAQ at http://www.orfeo-toolbox.org/FAQ.html You received this message because you are subscribed to the Google Groups "otb-users" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/otb-users?hl=en --- You received this message because you are subscribed to the Google Groups "otb-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
