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TADAnisotropicDiffusionCommand Class

Summary

An iterative filter that performs tensor-guided anisotropic diffusion in order to reduce noise while preserving the edges in the image.

Syntax

Java

Objective-C

WinRT C#

C++

public class TADAnisotropicDiffusionCommand : Leadtools.Imageprocessing.Leadtools.ImageProcessing.RasterCommand, Leadtools.Imageprocessing.Leadtools.ImageProcessing.IRasterCommand

Public Class TADAnisotropicDiffusionCommand  
   Inherits Leadtools.Imageprocessing.Leadtools.ImageProcessing.RasterCommand 
   Implements Leadtools.Imageprocessing.Leadtools.ImageProcessing.IRasterCommand

public sealed class TADAnisotropicDiffusionCommand : Leadtools.Imageprocessing.Leadtools.ImageProcessing.IRasterCommand

@interface LTTADAnisotropicDiffusionCommand : LTRasterCommand

public class TADAnisotropicDiffusionCommand extends RasterCommand

function Leadtools.ImageProcessing.Core.TADAnisotropicDiffusionCommand()

public ref class TADAnisotropicDiffusionCommand : public Leadtools.Imageprocessing.Leadtools.ImageProcessing.RasterCommand, Leadtools.Imageprocessing.Leadtools.ImageProcessing.IRasterCommand

Remarks

Three classes implement anisotropic diffusion:
AnisotropicDiffusionCommand. The AnisotropiDiffusionCommand is a slower but more accurate version of SRADAnisotropDiffusionCommand.
SRADAnisotropicDiffusionCommand. In comparison with conventional anisotropic diffusion, with the SRADAnisotropicDiffusionCommand uniform areas exhibit more smoothing and edges and features are preserved better.
TADAnisotropicDiffusionCommand. The TADAnisotropicDiffusionCommand employs an edge-seeking diffusion coefficient. Areas within regions are smoothed, but the edges are not affected.
Use the TADAnisotropicDiffusionCommand to reduce noise in images (more specifically, medical images). Performance is better than that of the Median or Gaussian Filters.
The number of iterations controls the number of times the filter will be applied to an image. The lower the number of iterations, the faster the filter will perform. Higher iterations typically mean clearer results.
This command can only process the entire image. It does not support regions.
This command supports 8, 16-bit grayscale images and 24, 32-bit colored images.
This command supports signed/unsigned images.

Example

Imports Leadtools 
Imports Leadtools.Codecs 
Imports Leadtools.ImageProcessing.Core 
 
    
Public Sub TADAnisotropicDiffusionCommandExample() 
   ' Load an image 
   Dim codecs As RasterCodecs = New RasterCodecs() 
   codecs.ThrowExceptionsOnInvalidImages = True 
   Dim image As RasterImage = codecs.Load(Path.Combine(LEAD_VARS.ImagesDir, "IMAGE3.dcm")) 
 
   ' Prepare the command 
   Dim command As TADAnisotropicDiffusionCommand = New TADAnisotropicDiffusionCommand() 
 
   ' Apply 
   command.Iterations = 10 
   command.Lambda = 14 
   command.Kappa = 30 
   command.Flags = TADAnisotropicDiffusionFlags.QuadraticFlux 
   command.Run(image) 
End Sub 
 
Public NotInheritable Class LEAD_VARS 
Public Const ImagesDir As String = "C:\Users\Public\Documents\LEADTOOLS Images" 
End Class

using Leadtools; 
using Leadtools.Codecs; 
using Leadtools.ImageProcessing.Core; 
 
       
public void TADAnisotropicDiffusionCommandExample() 
{ 
    // Load an image 
    RasterCodecs codecs = new RasterCodecs(); 
    codecs.ThrowExceptionsOnInvalidImages = true; 
    RasterImage image = codecs.Load(Path.Combine(LEAD_VARS.ImagesDir, "IMAGE3.dcm")); 
 
    // Prepare the command 
    TADAnisotropicDiffusionCommand command = new TADAnisotropicDiffusionCommand(); 
 
    // Apply 
    command.Iterations = 10; 
    command.Lambda = 14; 
    command.Kappa = 30; 
    command.Flags = TADAnisotropicDiffusionFlags.QuadraticFlux; 
    command.Run(image); 
} 
 
static class LEAD_VARS 
{ 
public const string ImagesDir = @"C:\Users\Public\Documents\LEADTOOLS Images"; 
}