Application for number of endmembers estimation in hyperspectral images.
There are two classes in OTB for estimating the number of endmembers in hyperspectral images, one implementing the virtual dimensionality algorithm and the other using the Eigenvalue Likelihood Maximization algorithm, but there are no application corresponding to these algorithm.
This MR adds an application for the endmember number estimation. The application
will first compute the covariance and correlation matrices of the input image using a
otb::StreamingStatisticsVectorImageFilter and then use a
VirtualDimensionality object with the computed statistics to output an estimation
of the number of endmembers.
Classes and files
otbEndmemberNumberEstimation.cxx where the new application is implemented.
A new application has been created :
EndmemberNumberEstimation, it has the following parameters :
in: input multi-channel image
number: number of endmembers
algo: chosen algorithm
elm: eigenvalue likelihood maximization
vd: virtual dimensionality
algo.vd.far: false alarm rate for the virtual dimensionality algorithm.
ram: ram parameter
New validation tests for both algorithms.
The copyright owner is CNES and has signed the ORFEO ToolBox Contributor License Agreement.
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