Smoothing
Brief Description
Apply a smoothing filter to an image
Tags
Image Filtering
Long Description
This application applies a smoothing filter to an image. Three methodes can be used : a gaussian filter , a mean filter , or an anisotropic diffusion using the Perona-Malik algorithm.
Parameters
Input Image (in): Input image to smooth.
Output Image (out): Output smoothed image.
Available RAM (Mb) (ram): Available memory for processing (in MB)
Smoothing Type (type): Smoothing kernel to apply
Mean (mean):
Radius (type.mean.radius): Kernel's radius (in pixels)
Gaussian (gaussian):
Radius (type.gaussian.radius): Standard deviation of the gaussian kernel used to filter the image
Anisotropic Diffusion (anidif):
Time Step (type.anidif.timestep): Time step that will be used to discretize the diffusion equation
Nb Iterations (type.anidif.nbiter): Number of iterations needed to get the result
Conductance (type.anidif.conductance): Controls the sensitivity of the conductance term in the diffusion equation. The lower it is the stronger the features will be preserved
Load otb application from xml file (inxml): Load otb application from xml file
Save otb application to xml file (outxml): Save otb application to xml file
Limitations
None
Authors
OTB-Team
See also
Example of use
in: Romania_Extract.tif
out: smoothedImage_mean.png uchar
type: mean
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
Image smoothing using a mean filter.
otbcli_Smoothing -in Romania_Extract.tif -out smoothedImage_mean.png uchar -type mean
Image smoothing using an anisotropic diffusion filter.
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