HyperspectralUnmixing - Hyperspectral data unmixing
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Estimate abundance maps from an hyperspectral image and a set of endmembers.

Detailed description
--------------------

The application applies a linear unmixing algorithmto an hyperspectral data cube. This method supposes that the mixture betweenaterials in the scene is macroscopic and simulates a linear mixing model ofspectra.

The Linear Mixing Model (LMM) acknowledges that reflectancespectrum associated with each pixel is a linear combination of purematerials in the recovery area, commonly known as endmembers. Endmembers canbe estimated using the VertexComponentAnalysis application.

The application allows to estimate the abundance maps with several algorithms :
  * Unconstrained Least Square (ucls)
  * Image Space Reconstruction Algorithm (isra)
  * Non-negative constrained
  * Least Square (ncls)
  * Minimum Dispersion Constrained Non Negative Matrix Factorization (MDMDNMF).

Parameters
----------

This section describes in details the parameters available for this application. Table [#]_ presents a summary of these parameters and the parameters keys to be used in command-line and programming languages. Application key is *HyperspectralUnmixing* .

.. [#] Table: Parameters table for Hyperspectral data unmixing.

+-------------+----------------------------------+--------------------------+
|Parameter Key|Parameter Name                    |Parameter Type            |
+=============+==================================+==========================+
|in           |Input Image Filename              |Input image               |
+-------------+----------------------------------+--------------------------+
|out          |Output Image                      |Output image              |
+-------------+----------------------------------+--------------------------+
|ie           |Input endmembers                  |Input image               |
+-------------+----------------------------------+--------------------------+
|ua           |Unmixing algorithm                |Choices                   |
+-------------+----------------------------------+--------------------------+
|ua ucls      |UCLS                              | *Choice*                 |
+-------------+----------------------------------+--------------------------+
|ua ncls      |NCLS                              | *Choice*                 |
+-------------+----------------------------------+--------------------------+
|ua isra      |ISRA                              | *Choice*                 |
+-------------+----------------------------------+--------------------------+
|ua mdmdnmf   |MDMDNMF                           | *Choice*                 |
+-------------+----------------------------------+--------------------------+
|inxml        |Load otb application from xml file|XML input parameters file |
+-------------+----------------------------------+--------------------------+
|outxml       |Save otb application to xml file  |XML output parameters file|
+-------------+----------------------------------+--------------------------+

- **Input Image Filename**: The hyperspectral data cube input.
- **Output Image**: The output abundance map. The abundance fraction are stored in a multispectral image where band N corresponds to the fraction of endmembers N in each pixel.
- **Input endmembers**: The endmembers (estimated pure pixels) to use for unmixing. Must be stored as a multispectral image, where each pixel is interpreted as an endmember.
- **Unmixing algorithm**: The algorithm to use for unmixing. Available choices are: 

 * **UCLS**: Unconstrained Least Square.
 * **NCLS**: Non-negative constrained Least Square.
 * **ISRA**: Image Space Reconstruction Algorithm.
 * **MDMDNMF**: Minimum Dispersion Constrained Non Negative Matrix Factorization.

- **Load otb application from xml file**: Load otb application from xml file.
- **Save otb application to xml file**: Save otb application to xml file.


Example
-------

To run this example in command-line, use the following: 
::

	otbcli_HyperspectralUnmixing -in cupriteSubHsi.tif -ie cupriteEndmembers.tif -out HyperspectralUnmixing.tif double -ua ucls

To run this example from Python, use the following code snippet: 

::

	#!/usr/bin/python

	# Import the otb applications package
	import otbApplication

	# The following line creates an instance of the HyperspectralUnmixing application 
	HyperspectralUnmixing = otbApplication.Registry.CreateApplication("HyperspectralUnmixing")

	# The following lines set all the application parameters:
	HyperspectralUnmixing.SetParameterString("in", "cupriteSubHsi.tif")

	HyperspectralUnmixing.SetParameterString("ie", "cupriteEndmembers.tif")

	HyperspectralUnmixing.SetParameterString("out", "HyperspectralUnmixing.tif")
	HyperspectralUnmixing.SetParameterOutputImagePixelType("out", 7)

	HyperspectralUnmixing.SetParameterString("ua","ucls")

	# The following line execute the application
	HyperspectralUnmixing.ExecuteAndWriteOutput()

Limitations
~~~~~~~~~~~

None

Authors
~~~~~~~

This application has been written by OTB-Team.

See Also
~~~~~~~~

These additional resources can be useful for further information: 
  | VertexComponentAnalysis