SOMClassification otbcli_SOMClassification SOM Classification Learning SOM image classification. ParameterRaster in InputImage Input image to classify. False OutputRaster out OutputImage Output classified image (each pixel contains the index of its corresponding vector in the SOM). ParameterRaster vm ValidityMask Validity mask (only pixels corresponding to a mask value greater than 0 will be used for learning) True ParameterNumber tp TrainingProbability Probability for a sample to be selected in the training set 1 ParameterNumber ts TrainingSetSize Maximum training set size (in pixels) 0 ParameterNumber sl StreamingLines Number of lines in each streaming block (used during data sampling) 0 OutputRaster som SOM Map Output image containing the Self-Organizing Map ParameterNumber sx SizeX X size of the SOM map 32 ParameterNumber sy SizeY Y size of the SOM map 32 ParameterNumber nx NeighborhoodX X size of the initial neighborhood in the SOM map 10 ParameterNumber ny NeighborhoodY Y size of the initial neighborhood in the SOM map 10 ParameterNumber ni NumberIteration Number of iterations for SOM learning 5 ParameterNumber bi BetaInit Initial learning coefficient 1 ParameterNumber bf BetaFinal Final learning coefficient 0.1 ParameterNumber iv InitialValue Maximum initial neuron weight 0 ParameterNumber ram Available RAM (Mb) Available memory for processing (in MB) 128 ParameterNumber rand set user defined seed Set specific seed. with integer value. 0