SRADAnisotropicDiffusionCommand Class

Summary

Applies a 2-Dimensional Anisotropic Diffusion filter on an image in order to reduce noise and speckling.

Syntax

Objective-C

C++/CLI

Java

Python

public class SRADAnisotropicDiffusionCommand : RasterCommand

@interface LTSRADAnisotropicDiffusionCommand : LTRasterCommand

public class SRADAnisotropicDiffusionCommand 
    extends RasterCommand

public ref class SRADAnisotropicDiffusionCommand : public RasterCommand

class SRADAnisotropicDiffusionCommand(RasterCommand):

Remarks

The SRADAnisotropicDiffusionCommand (Speckle Reducing Anisotropic Diffusion) reduces noise and speckling in images while preserving the edges.
The number of iterations controls the number of times the filter will be applied to the image. The lower the number of iterations, the faster the filter will perform. Higher iterations typically mean clearer results.
This command processes only 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

Java

using Leadtools; 
using Leadtools.Codecs; 
using Leadtools.ImageProcessing.Core; 
 
public void SRADAnisotropicDiffusionCommandExample() 
{ 
   // Load an image 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.ThrowExceptionsOnInvalidImages = true; 
 
   RasterImage image = codecs.Load(Path.Combine(LEAD_VARS.ImagesDir, "IMAGE3.dcm")); 
 
   // Prepare the command 
   SRADAnisotropicDiffusionCommand command = new SRADAnisotropicDiffusionCommand(); 
 
   // Apply 
   command.Iterations = 10; 
   command.Lambda = 50; 
   command.Rect = new LeadRect(150, 300, 30, 30); 
   command.Run(image); 
} 
 
static class LEAD_VARS 
{ 
   public const string ImagesDir = @"C:\LEADTOOLS23\Resources\Images"; 
}

 
import java.io.File; 
import java.io.IOException; 
 
import org.junit.*; 
import org.junit.runner.JUnitCore; 
import org.junit.runner.Result; 
import org.junit.runner.notification.Failure; 
import static org.junit.Assert.assertTrue; 
 
import leadtools.*; 
import leadtools.codecs.*; 
import leadtools.imageprocessing.core.SRADAnisotropicDiffusionCommand; 
 
 
public void sradAnisotropicDiffusionCommandExample() { 
   final String LEAD_VARS_IMAGES_DIR = "C:\\LEADTOOLS23\\Resources\\Images"; 
 
   // Load an image 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.setThrowExceptionsOnInvalidImages(true); 
 
   RasterImage image = codecs.load(combine(LEAD_VARS_IMAGES_DIR, "DICOM\\IMAGE3.dcm")); 
 
   // Prepare the command 
   SRADAnisotropicDiffusionCommand command = new SRADAnisotropicDiffusionCommand(); 
 
   // Apply 
   command.setIterations(10); 
   command.setLambda(50); 
   command.setRect(new LeadRect(150, 300, 30, 30)); 
   int change = command.run(image); 
   assertTrue(change != RasterImageChangedFlags.NONE); 
 
   String outputFileName = combine(LEAD_VARS_IMAGES_DIR, "DICOM\\IMAGE3_result.dcm"); 
   codecs.save(image, outputFileName, RasterImageFormat.DICOM_JPEG_COLOR, 0); 
   System.out.println("Command run, image saved to " + outputFileName); 
}

Requirements

Target Platforms

Reference

SRADAnisotropicDiffusionCommand Members

Leadtools.ImageProcessing.Core Namespace

AnisotropicDiffusionCommand Class

TADAnisotropicDiffusionCommand Class

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Help Version 23.0.2024.3.3

Leadtools.ImageProcessing.Core Assembly

Introduction

Getting Started

Namespaces

Leadtools.ImageProcessing.Core Namespace

Assemblies