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 | 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.