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 [1] presents a summary of these parameters and the parameters keys to be used in command-line and programming languages. Application key is Smoothing .

[1]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 Choice Mean
type gaussian Choice Gaussian
type anidif Choice Anisotropic Diffusion
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.