.. _VertexComponentAnalysis: 

VertexComponentAnalysis
=======================





Given a set of mixed spectral vectors, estimate reference substances also known as endmembers using the Vertex Component Analysis algorithm.

Description
-----------

Apply the Vertex Component Analysis [1] to an hyperspectral image to extract endmembers. Given a set of mixed spectral vectors (multispectral or hyperspectral), the application estimates the spectral signature of reference substances also known as endmembers.



Parameters
----------

.. contents:: :local:

.. |br| raw:: html

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.. |em| raw:: html

   &emsp;

**Input Image** :code:`-in image` *Mandatory* |br|
Input hyperspectral data cube

**Output Endmembers** :code:`-outendm image [dtype]` *Mandatory* |br|
Endmembers, stored in a one-line multi-spectral image.Each pixel corresponds to one endmembers and each band values corresponds to the spectral signature of the corresponding endmember.

**Number of endmembers** :code:`-ne int` *Default value: 1* |br|
The number of endmembers to extract from the hyperspectral image.

**Random seed** :code:`-rand int` |br|
Set a specific random seed with integer value.



Examples
--------

From the command-line:

.. code-block:: bash

    otbcli_VertexComponentAnalysis -in cupriteSubHsi.tif -ne 5 -outendm VertexComponentAnalysis.tif double


From Python:

.. code-block:: python

	import otbApplication

	app = otbApplication.Registry.CreateApplication("VertexComponentAnalysis")

	app.SetParameterString("in", "cupriteSubHsi.tif")
	app.SetParameterInt("ne", 5)
	app.SetParameterString("outendm", "VertexComponentAnalysis.tif")
	app.SetParameterOutputImagePixelType("outendm", 7)

	app.ExecuteAndWriteOutput()





See also
--------

| [1] J. M. P. Nascimento and J. M. B. Dias, Vertex component analysis: a fast algorithm to unmix hyperspectral data, in IEEE Transactions on Geoscience and Remote Sensing, vol. 43, no. 4, pp. 898-910, April 2005.J. M. P. Nascimento and J. M. B. Dias, Vertex component analysis: a fast algorithm to unmix hyperspectral data, in IEEE Transactions on Geoscience and Remote Sensing, vol. 43, no. 4, pp. 898-910, April 2005.