Dear Manuel, Agus, users I have found very useful also to read Comaniciu and Meer paper Mean Shift: A Robust Approach Toward Feature Space Analysis <http://ieeexplore.ieee.org/document/1000236/?tp=&arnumber=1000236> (possible to find here <https://courses.csail.mit.edu/6.869/handouts/PAMIMeanshift.pdf>). It is describing general mean-shift as well as *joint domain of spectral and spatial features*. From both papers I can conclude now (please correct me, where I am wrong):
there are 2 steps: * *filtering* / filtering step -- 1st step of LSMS * described in [1, section 4.1], [2, section IV.B p. 957 and section IV.D p. 958], [2, section 5.B.1 p. 960] * here spatial and range radius (*h_s* and *h_r* in [2]) control the *bandwidth of a kernel* (eq. 35 of Comaniciu paped) -- it select "close" pixels (spectrally and spatially) to compute mean shift vector directing to mode in each iteration * *segmentation* / grouping step -- 2nd step of LSMS * described in [1, section 4.2], [2, section IV B p. 957 and section IV D p. 958], [2, section 5.B.2 p. 960] * here spatial and range radius (*h'_s* and *h'_r* in [2]) control which *mode(s) selection* resp. which mode(s) will represent the (unknown) pixel (in [1] mentioned as "Significant mode" on p. 612) (in [2] mentioned as spatial modes closer than h_s and spectral modes closer than h_r on p. 957 and denoted as h'_s and h'_r in step 2 on p. 958) But I still do not fully understand 2 band raster "displacement map" resulting from 1st step of LSMS. I have one more question... in [1] there is mentioned, that some transformation (L*u*v or L*a*b) may be necessary to correctly represent color data. Is such a transformation implemented in 4 step LSMS? Resp. I am segmenting 3 bands raster composed from spring resp. summer resp. autumn NDVI bands... Those values are from <-1; 1> not <0; 255> like some RGB. Should I perform some transformation? Because my ranger need to be typically very small (0.02) and pixel values in "displacement map" has 0 very often. cited papers: [1] Dorin Comaniciu and Peter Meer. 2002. Mean Shift: A Robust Approach Toward Feature Space Analysis. *IEEE Trans. Pattern Anal. Mach. Intell.* 24, 5 (May 2002), 603-619. DOI=http://dx.doi.org/10.1109/34.1000236 [2] Michel J, Youssefi D, Grizonnet M. 2015. Stable mean-shift algorithm and its application to the segmentation of arbitrarily large remote sensing images *Ieee Transactions On Geoscience and Remote Sensing*. 53: 952-964. DOI: 10.1109/TGRS.2014.2330857 <http://doi.org/10.1109/TGRS.2014.2330857> Best regards, Jiří. On Tuesday, 6 September 2016 15:50:58 UTC+2, Jiří Fejfar wrote: > > 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%7Csort: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.
