.. _HyperspectralUnmixing: 

HyperspectralUnmixing
=====================





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

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

The application applies a linear unmixing algorithm to an hyperspectral data cube. This method supposes that the mixture between aterials in the scene is macroscopic and simulates a linear mixing model of spectra.

The Linear Mixing Model (LMM) acknowledges that reflectance spectrum associated with each pixel is a linear combination of pure materials in the recovery area, commonly known as endmembers. Endmembers can be estimated using the :ref:`VertexComponentAnalysis` application.

The application allows estimating the abundance maps with several algorithms:

* Unconstrained Least Square (ucls)
* Image Space Reconstruction Algorithm (isra)
* Least Square (ncls)
* Minimum Dispersion Constrained Non Negative Matrix Factorization (MDMDNMF).



Parameters
----------

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.. |em| raw:: html

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

**Output Image** :code:`-out image [dtype]` *Mandatory* |br|
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** :code:`-ie image` *Mandatory* |br|
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** :code:`-ua [ucls|isra|mdmdnmf]` *Default value: ucls* |br|
The algorithm to use for unmixing

* **UCLS** |br| Unconstrained Least Square

* **ISRA** |br| Image Space Reconstruction Algorithm

* **MDMDNMF** |br| Minimum Dispersion Constrained Non Negative Matrix Factorization





Examples
--------

From the command-line:

.. code-block:: bash

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


From Python:

.. code-block:: python

	import otbApplication

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

	app.SetParameterString("in", "cupriteSubHsi.tif")
	app.SetParameterString("ie", "cupriteEndmembers.tif")
	app.SetParameterString("out", "HyperspectralUnmixing.tif")
	app.SetParameterOutputImagePixelType("out", 7)
	app.SetParameterString("ua","ucls")

	app.ExecuteAndWriteOutput()





See also
--------

| :ref:`VertexComponentAnalysis`