Summary
Application for number of endmembers estimation in hyperspectral images.
Rationale
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 EigenvalueLikelihoodMaximisation
or a VirtualDimensionality object with the computed statistics to output an estimation
of the number of endmembers.
Implementation Details
Classes and files
New file otbEndmemberNumberEstimation.cxx where the new application is implemented.
Applications
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
Tests
New validation tests for both algorithms.
Copyright
The copyright owner is CNES and has signed the ORFEO ToolBox Contributor License Agreement.
Check before merging:
- All discussions are resolved
- At least 2
👍 votes from core developers, no👎 vote. - The feature branch is (reasonably) up-to-date with the base branch
- Dashboard is green
- Copyright owner has signed the ORFEO ToolBox Contributor License Agreement