* Mean shift can be used for edge-preserving smoothing, or for clustering. The GetOutput() method
* return concatenation of spatial and spectral meanshift filtered data GetSpatialOutput() and GetSpectralOutput() gives
* resp. spatial and Spectral filtering parts
* return spatial and meanshift filtered data GetSpatialOutput() and GetRangeOutput() gives
* resp. spatial (as displacement map) and Spectral filtering parts
*
*
* GetMetricOutput() method gives mean shift vector
* GetMetricOutput() method gives mean shift vector after pixel convergence.
* GetIterationOutput() returns the number of iterations performed for each pixel.
* GetLabelOutput() returns a label map with one label for each mode.
*
* MeanShifVector norm is compared with Threshold (set using Get/Set accessor) to define pixel convergence (1e-3 by default).
* MaxIterationNumber defines maximum iteration number for each pixel convergence (set using Get/Set accessor). Set to 4 by default.
* ModeSearchOptimization is a boolean value, to choose between optimized and non optimized algorithm. If set to true (by default), assign mode value to each pixel on a path covered in convergence steps.
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* For more information on mean shift techniques, one might consider reading the following article:
