Smoothing - Smoothing
^^^^^^^^^^^^^^^^^^^^^

Apply a smoothing filter to an image

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

This application applies smoothing filter to an image. Either gaussian, mean, or anisotropic diffusion are available.

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 *Smoothing* .

.. [#] Table: Parameters table for Smoothing.

+-----------------------+----------------------------------+--------------------------+
|Parameter Key          |Parameter Name                    |Parameter Type            |
+=======================+==================================+==========================+
|in                     |Input Image                       |Input image               |
+-----------------------+----------------------------------+--------------------------+
|out                    |Output Image                      |Output image              |
+-----------------------+----------------------------------+--------------------------+
|ram                    |Available RAM (Mb)                |Int                       |
+-----------------------+----------------------------------+--------------------------+
|type                   |Smoothing Type                    |Choices                   |
+-----------------------+----------------------------------+--------------------------+
|type mean              |Mean                              | *Choice*                 |
+-----------------------+----------------------------------+--------------------------+
|type gaussian          |Gaussian                          | *Choice*                 |
+-----------------------+----------------------------------+--------------------------+
|type anidif            |Anisotropic Diffusion             | *Choice*                 |
+-----------------------+----------------------------------+--------------------------+
|type.mean.radius       |Radius                            |Int                       |
+-----------------------+----------------------------------+--------------------------+
|type.gaussian.radius   |Radius                            |Float                     |
+-----------------------+----------------------------------+--------------------------+
|type.anidif.timestep   |Time Step                         |Float                     |
+-----------------------+----------------------------------+--------------------------+
|type.anidif.nbiter     |Nb Iterations                     |Int                       |
+-----------------------+----------------------------------+--------------------------+
|type.anidif.conductance|Conductance                       |Float                     |
+-----------------------+----------------------------------+--------------------------+
|inxml                  |Load otb application from xml file|XML input parameters file |
+-----------------------+----------------------------------+--------------------------+
|outxml                 |Save otb application to xml file  |XML output parameters file|
+-----------------------+----------------------------------+--------------------------+

**Input Image**: Input image to smooth.

**Output Image**: Output smoothed image.

**Available RAM (Mb)**: Available memory for processing (in MB).

**Smoothing Type**: Smoothing kernel to apply. Available choices are: 

- **Mean**

 * **Radius**: Mean radius (in pixels).

- **Gaussian**

 * **Radius**: Gaussian radius (in pixels).

- **Anisotropic Diffusion**

 * **Time Step**: Diffusion equation time step.
 * **Nb Iterations**: Controls the sensitivity of the conductance term.
 * **Conductance**


**Load otb application from xml file**: Load otb application from xml file.

**Save otb application to xml file**: Save otb application to xml file.



Examples
--------


:Example 1:

Image smoothing using a mean filter.To run this example in command-line, use the following: 

::

	otbcli_Smoothing -in Romania_Extract.tif -out smoothedImage_mean.png uchar -type mean

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 Smoothing application 
	Smoothing = otbApplication.Registry.CreateApplication("Smoothing")

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

	Smoothing.SetParameterString("out", "smoothedImage_mean.png")
	Smoothing.SetParameterOutputImagePixelType("out", 1)

	Smoothing.SetParameterString("type","mean")

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

:Example 2:

Image smoothing using an anisotropic diffusion filter.To run this example in command-line, use the following: 

::

	otbcli_Smoothing -in Romania_Extract.tif -out smoothedImage_ani.png float -type anidif -type.anidif.timestep 0.1 -type.anidif.nbiter 5 -type.anidif.conductance 1.5

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 Smoothing application 
	Smoothing = otbApplication.Registry.CreateApplication("Smoothing")

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

	Smoothing.SetParameterString("out", "smoothedImage_ani.png")
	Smoothing.SetParameterOutputImagePixelType("out", 6)

	Smoothing.SetParameterString("type","anidif")

	Smoothing.SetParameterFloat("type.anidif.timestep", 0.1)

	Smoothing.SetParameterInt("type.anidif.nbiter", 5)

	Smoothing.SetParameterFloat("type.anidif.conductance", 1.5)

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

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

None

Authors
~~~~~~~

This application has been written by OTB-Team.