SOM image classification.
Unsupervised Self Organizing Map image classification.
InputImage (in): Input image to classify.
OutputImage (out): Output classified image (each pixel contains the index of its corresponding vector in the SOM).
ValidityMask (vm): Validity mask (only pixels corresponding to a mask value greater than 0 will be used for learning)
TrainingProbability (tp): Probability for a sample to be selected in the training set
TrainingSetSize (ts): Maximum training set size (in pixels)
SOM Map (som): Output image containing the Self-Organizing Map
SizeX (sx): X size of the SOM map
SizeY (sy): Y size of the SOM map
NeighborhoodX (nx): X size of the initial neighborhood in the SOM map
NeighborhoodY (ny): Y size of the initial neighborhood in the SOM map
NumberIteration (ni): Number of iterations for SOM learning
BetaInit (bi): Initial learning coefficient
BetaFinal (bf): Final learning coefficient
InitialValue (iv): Maximum initial neuron weight
Available RAM (Mb) (ram): Available memory for processing (in MB)
set user defined seed (rand): Set specific seed. with integer value.
Load otb application from xml file (inxml): Load otb application from xml file
Save otb application to xml file (outxml): Save otb application to xml file
Example of use
otbcli_SOMClassification -in QB_1_ortho.tif -out SOMClassification.tif -tp 1.0 -ts 16384 -sx 32 -sy 32 -nx 10 -ny 10 -ni 5 -bi 1.0 -bf 0.1 -iv 0